SlideShare une entreprise Scribd logo
1  sur  102
An Introduction
What’s in it for you?
What is Clustering?
What is Hierarchical Clustering?
How Hierarchical Clustering works?
Distance Measure
What is Agglomerative Clustering?
What is Divisive Clustering?
What is Clustering?
What is Clustering?
I have 20 places to cover in 4 days!
What is Clustering?
How will I manage to cover all?
What is Clustering?
You can make use of clustering by
grouping the data into four clusters
What is Clustering?
Each of these clusters will have places
which are close by
What is Clustering?
Then each day you can visit one group
and cover all places in the group
What is Clustering?
Great!
What is Clustering?
It will group places with least distance
The method of dividing the objects into clusters which are similar between them and are dissimilar
to the objects belonging to another cluster
What is Clustering?
It will group places with least distance
The method of dividing the objects into clusters which are similar between them and are dissimilar
to the objects belonging to another cluster
Partial
Clustering
Hierarchical
Clustering
What is Clustering?
It will group places with least distance
The method of dividing the objects into clusters which are similar between them and are dissimilar
to the objects belonging to another cluster
Partial
Clustering
Hierarchical
Clustering
Agglomerative Divisive
What is Clustering?
It will group places with least distance
The method of dividing the objects into clusters which are similar between them and are dissimilar
to the objects belonging to another cluster
Partial
Clustering
Hierarchical
Clustering
Agglomerative Divisive K-means Fuzzy C-Means
What is Clustering?
Applications of Clustering
Customer
Segmentation
What is Clustering?
Customer
Segmentation Insurance
Applications of Clustering
What is Clustering?
Insurance City Planning
Applications of Clustering
Customer
Segmentation
Hierarchical Clustering
What is Hierarchical Clustering?
It will group places with least distance
Let’s consider that we have a set of cars and we have to group similar ones together
What is Hierarchical Clustering?
It will group places with least distance
Hierarchical Clustering creates a tree like structure and group similar objects together
What is Hierarchical Clustering?
It will group places with least distance
The grouping is done till we reach the last cluster
What is Hierarchical Clustering?
It will group places with least distance
Hierarchical Clustering is separating data into different groups based on some measure of similarity
Types of Hierarchical Clustering
It will group places with least distance
Agglomerative
It is known as Bottom-up approach
Types of Hierarchical Clustering
It will group places with least distance
Agglomerative Divisive
It is known as Top Down approach
How Hierarchical Clustering works?
What is Hierarchical Clustering?
Convergence
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
Termination
Grouping
Measure the
distance
• Let’s consider we have few points on a plane
What is Hierarchical Clustering?
Convergence
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
Termination
Grouping
Measure the
distance
• Each data point is a cluster of its own
What is Hierarchical Clustering?
Convergence
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
Termination
Grouping
Measure the
distance
• Each data point is a cluster of its own
• We try to find the least distance between two data points/cluster
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
• The two nearest clusters/datapoints are merged together
Termination
Grouping
Measure the
distance
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
• The two nearest clusters/datapoints are merged together
Termination
Grouping
Measure the
distance
P2 P1
• This is represented in a tree like structure called Dendrogram
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
• The two nearest clusters/datapoints are merged together
Termination
Grouping
Measure the
distance
• This is represented in a tree like structure called Dendrogram
P3P2 P1 P4
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
P5 P6
• The two nearest clusters/datapoints are merged together
Termination
Grouping
Measure the
distance
• This is represented in a tree like structure called Dendrogram
P5 P6P3 P4P2 P1
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
P5 P6
• The two nearest clusters/datapoints are merged together
Termination
Grouping
Measure the
distance
• This is represented in a tree like structure called Dendrogram
P5 P6P3 P4P2 P1
What is Hierarchical Clustering?
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P3
P4
P5 P6
0
0.2
0.4
0.6
0.8
1
1.2
0 0.5 1 1.5
Y-Values
P6
P3
P4
P6
• We terminate when we are left with only one clusters
Termination
Grouping
Measure the
distance
P6P3P2 P1
P
P5P4
What is Hierarchical Clustering?
It will group places with least distance
An algorithm that builds hierarchy of clusters
0
1
2
3
4
5
6
0 2 4 6 8
Y-Values
P1P2
P5 P6
P3
P4
P5 P6 P2 P1 P3 P4
?
How do we measure the distance
between the data points?
Distance Measure
Distance Measure
Distance measure will determine the similarity between two elements and it will influence the shape of
the clusters
Distance Measure
Euclidean
distance
measure
Distance measure will determine the similarity between two elements and it will influence the shape of
the clusters
Distance Measure
Euclidean
distance
measure
Squared Euclidean
distance measure
Distance measure will determine the similarity between two elements and it will influence the shape of
the clusters
Distance Measure
Euclidean
distance
measure
Manhattan
distance
measure
Squared Euclidean
distance measure
Distance measure will determine the similarity between two elements and it will influence the shape of
the clusters
Distance Measure
Euclidean
distance
measure
Manhattan
distance
measure
Squared Euclidean
distance measure
Cosine distance
measure
Distance measure will determine the similarity between two elements and it will influence the shape of
the clusters
Euclidean Distance Measure
• The Euclidean distance is the "ordinary" straight line
• It is the distance between two points in Euclidean space
d=√ 𝑖=1
𝑛
( 𝑞𝑖− )2
p
q
Euclidian
Distance
𝑝𝑖
Option 02
Euclidean distance
measure
01
Squared euclidean
distance measure
02
Manhattan distance
measure
03
Cosine distance
measure
04
Squared Euclidean Distance Measure
The Euclidean squared distance metric uses the same equation as the
Euclidean distance metric, but does not take the square root.
d= 𝑖=1
𝑛
( 𝑞𝑖− )2
𝑝𝑖
Option 02
Euclidean distance
measure
01
Squared euclidean
distance measure
02
Manhattan distance
measure
03
Cosine distance
measure
04
Manhattan Distance Measure
Option 02
Euclidean distance
measure
01
Squared euclidean
distance measure
02
Manhattan distance
measure
03
Cosine distance
measure
04
The Manhattan distance is the simple sum of the horizontal and vertical
components or the distance between two points measured along axes at right angles
d= 𝑖=1
𝑛
| 𝑞 𝑥− |
p
q
Manhattan
Distance
𝑝 𝑥 +|𝑞 𝑦− |𝑝 𝑦
(x,y)
(x,y)
Cosine Distance Measure
Option 02
Euclidean distance
measure
01
Squared euclidean
distance measure
02
Manhattan distance
measure
03
Cosine distance
measure
04
The cosine distance similarity measures the angle between the two vectors
p
q
Cosine
Distance
𝑖=0
𝑛−1
𝑞𝑖−
𝑖=0
𝑛−1
(𝑞𝑖)2
× 𝑖=0
𝑛−1
(𝑝𝑖)2
d=
𝑝 𝑥
Agglomerative Clustering
What is Agglomerative Clustering?
It will group places with least distance
Agglomerative Clustering begins with each element as a separate cluster and merge them into larger clusters
What is Agglomerative Clustering?
It will group places with least distance
There are three key questions that needs to be answered
How do we represent a cluster of more than one point?
What is Agglomerative Clustering?
It will group places with least distance
There are three key questions that needs to be answered
How do we determine the nearness of clusters?
How do we represent a cluster of more than one point?
What is Agglomerative Clustering?
It will group places with least distance
There are three key questions that needs to be answered
How do we represent a cluster of more than one point?
How do we determine the nearness of clusters?
When to stop combining clusters?
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
?
How do we
represent a cluster
of more than one
point?
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
We make use of
centroids which is
the average of it’s
points
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
(4.5,0.5)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
(4.5,0.5)
(1,1)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
(4.5,0.5)
(4.7,1.3)
(1,1)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
(4.5,0.5)
(4.7,1.3)
(1,1)
What is Agglomerative Clustering?
It will group places with least distance
(1,2)
(2,1)
(0,0)
(4,1)
(5,3)
(5,0)
Let’s assume that we have 6 points in a Euclidean space
(1.5,1.5)
(4.5,0.5)
(4.7,1.3)
(1,1)
?
When to stop
combining clusters?
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 1: Pick a number of clusters(k) upfront
We decide the number of clusters required in the beginning and we terminate when we
reach the value(k)
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Possible Challenges
 This only makes sense when we know about the data
Approach 1: Pick a number of clusters(k) upfront
We decide the number of clusters required in the beginning and we terminate when we
reach the value(k)
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
But, how is cohesion
defined?
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
Approach 3.1: Diameter of a cluster
• Diameter is the maximum distance between any pair of points in cluster
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
Approach 3.1: Diameter of a cluster
• Diameter is the maximum distance between any pair of points in cluster
• We terminate when the diameter of a new cluster exceeds the threshold
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
Approach 3.1: Radius of a cluster
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
Approach 3.1: Radius of a cluster
• Radius is the maximum distance of a point from centroid
What is Agglomerative Clustering?
It will group places with least distance
There are many approaches to it
Approach 2: Stop when the next merge would create a cluster with low “cohesion”
We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
?
Approach 3.1: Radius of a cluster
• Radius is the maximum distance of a point from centroid
• We terminate when the diameter of a new cluster exceeds the threshold
Divisive Clustering
What is Divisive Clustering?
It will group places with least distance
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
Step 2
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• Split it into different clustersStep 2
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 2
Step 1
• Start with a single cluster composed of all the data points
• This can be done using Monothethic divisive methods
• Split it into different clusters
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• Split this into different clusters
• This can be done using Monothethic divisive methods
Step 2
?
What is monothetic divisive method?
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• There are two ways to do this
1. Monothethic divisive methods
2. Polythetic divisive methods
?
A,B,C,D,E,F
• Obtain all possible splits into two clusters
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
• Obtain all possible splits into two clusters
A,B,C,D,E,F
C,D,E,F
A,B
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• Split this into different clusters
• There are two ways to do this
?
• Obtain all possible splits into two clusters
A,B,C,D,E,F
A,D,F
C,D,E,F
A,B
B,C,E
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• Split this into different clusters
• There are two ways to do this
1. Monothethic divisive methods
2. Polythetic divisive methods
?
• Obtain all possible splits into two clusters
A,B,C,D,E,F
A,D,F
C,D,E,F
A,B
B,C,E
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
A,B,C
D,E,F
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• There are two ways to do this
1. Monothethic divisive methods
2. Polythetic divisive methods
?
• For each split compute cluster sum of squares
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
• There are two ways to do this
1. Monothethic divisive methods
2. Polythetic divisive methods
?
• For each split compute cluster sum of squares
• We select the cluster with largest sum of squares
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
• Let’s assume that the sum of squared distance is largest for 3rd split
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
• We divide it into two clusters
A,B,C
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
A,B,C D,E,F
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
• We divide it into two clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
A,B,C D,E,F
A B,C
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
• We divide it into two clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
A,B,C D,E,F
A B,C
A,B,C,D,E,F
A,B,C D,E,F
A B,C D E,F
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
• We divide it into two clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
A,B,C D,E,F
A B,C D E,F
A B C
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
• We divide it into two clusters
What is Divisive Clustering?
It will group places with least distance
Convergence
Step 1
• Start with a single cluster composed of all the data points
?
• We terminate when every data point is it’s own cluster
A,B,C D,E,F
A B,C D E,F
A B C D E F
A,B,C,D,E,F
Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
Demo: Hierarchical Clustering
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
?Steps?
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Import the dataset
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Create a scatter plot
• Import the dataset
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Create a scatter plot
• Import the dataset
• Normalize the data
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Create a scatter plot
• Import the dataset
• Normalize the data
• Calculate Euclidean Distance
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Create a scatter plot
• Import the dataset
• Normalize the data
• Calculate Euclidean Distance
• Create a dendogram
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• Create a scatter plot
• Import the dataset
• Normalize the data
• Calculate Euclidean Distance
• Create a dendogram
• Cluster into groups
Demo: Hierarchical Clustering
Problem Statement
• To group petroleum companies based on their sales
Steps?
• output
So what’s
your next step?
So what’s
your next step?

Contenu connexe

Tendances

Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...Simplilearn
 
Unsupervised learning clustering
Unsupervised learning clusteringUnsupervised learning clustering
Unsupervised learning clusteringArshad Farhad
 
Unit 2 unsupervised learning.pptx
Unit 2 unsupervised learning.pptxUnit 2 unsupervised learning.pptx
Unit 2 unsupervised learning.pptxDr.Shweta
 
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...What is Machine Learning | Introduction to Machine Learning | Machine Learnin...
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...Simplilearn
 
Classification and Clustering
Classification and ClusteringClassification and Clustering
Classification and ClusteringEng Teong Cheah
 
05 Clustering in Data Mining
05 Clustering in Data Mining05 Clustering in Data Mining
05 Clustering in Data MiningValerii Klymchuk
 
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...Simplilearn
 
1.8 discretization
1.8 discretization1.8 discretization
1.8 discretizationKrish_ver2
 
K-Nearest Neighbor Classifier
K-Nearest Neighbor ClassifierK-Nearest Neighbor Classifier
K-Nearest Neighbor ClassifierNeha Kulkarni
 
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | Edureka
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | EdurekaSVM Algorithm Explained | Support Vector Machine Tutorial Using R | Edureka
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | EdurekaEdureka!
 
Hierarchical clustering
Hierarchical clusteringHierarchical clustering
Hierarchical clusteringChakrit Phain
 
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...Edureka!
 
Types of clustering and different types of clustering algorithms
Types of clustering and different types of clustering algorithmsTypes of clustering and different types of clustering algorithms
Types of clustering and different types of clustering algorithmsPrashanth Guntal
 
Classification in data mining
Classification in data mining Classification in data mining
Classification in data mining Sulman Ahmed
 

Tendances (20)

Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Da...
 
Unsupervised learning clustering
Unsupervised learning clusteringUnsupervised learning clustering
Unsupervised learning clustering
 
K means Clustering Algorithm
K means Clustering AlgorithmK means Clustering Algorithm
K means Clustering Algorithm
 
Unit 2 unsupervised learning.pptx
Unit 2 unsupervised learning.pptxUnit 2 unsupervised learning.pptx
Unit 2 unsupervised learning.pptx
 
Hierarchical Clustering
Hierarchical ClusteringHierarchical Clustering
Hierarchical Clustering
 
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...What is Machine Learning | Introduction to Machine Learning | Machine Learnin...
What is Machine Learning | Introduction to Machine Learning | Machine Learnin...
 
Classification and Clustering
Classification and ClusteringClassification and Clustering
Classification and Clustering
 
05 Clustering in Data Mining
05 Clustering in Data Mining05 Clustering in Data Mining
05 Clustering in Data Mining
 
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
 
1.8 discretization
1.8 discretization1.8 discretization
1.8 discretization
 
K-Nearest Neighbor Classifier
K-Nearest Neighbor ClassifierK-Nearest Neighbor Classifier
K-Nearest Neighbor Classifier
 
K Nearest Neighbors
K Nearest NeighborsK Nearest Neighbors
K Nearest Neighbors
 
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | Edureka
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | EdurekaSVM Algorithm Explained | Support Vector Machine Tutorial Using R | Edureka
SVM Algorithm Explained | Support Vector Machine Tutorial Using R | Edureka
 
Hierarchical clustering
Hierarchical clusteringHierarchical clustering
Hierarchical clustering
 
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorith...
 
Cluster analysis
Cluster analysisCluster analysis
Cluster analysis
 
Types of clustering and different types of clustering algorithms
Types of clustering and different types of clustering algorithmsTypes of clustering and different types of clustering algorithms
Types of clustering and different types of clustering algorithms
 
Classification in data mining
Classification in data mining Classification in data mining
Classification in data mining
 
Outlier Detection
Outlier DetectionOutlier Detection
Outlier Detection
 
K mean-clustering
K mean-clusteringK mean-clustering
K mean-clustering
 

Similaire à Hierarchical Clustering | Hierarchical Clustering in R |Hierarchical Clustering Example |Simplilearn

Chap8 basic cluster_analysis
Chap8 basic cluster_analysisChap8 basic cluster_analysis
Chap8 basic cluster_analysisguru_prasadg
 
Data mining Techniques
Data mining TechniquesData mining Techniques
Data mining TechniquesSulman Ahmed
 
Hierarchical methods navdeep kaur newww.pptx
Hierarchical methods navdeep kaur newww.pptxHierarchical methods navdeep kaur newww.pptx
Hierarchical methods navdeep kaur newww.pptxdhaliwalharsh055
 
Cluster Analysis
Cluster Analysis Cluster Analysis
Cluster Analysis Baivab Nag
 
01 Statistika Lanjut - Cluster Analysis part 1 with sound (1).pptx
01 Statistika Lanjut - Cluster Analysis  part 1 with sound (1).pptx01 Statistika Lanjut - Cluster Analysis  part 1 with sound (1).pptx
01 Statistika Lanjut - Cluster Analysis part 1 with sound (1).pptxniawiya
 
Slide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptSlide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptSandinoBerutu1
 
Slide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptSlide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptImXaib
 
Data mining and warehousing
Data mining and warehousingData mining and warehousing
Data mining and warehousingSwetha544947
 
Cluster Analysis
Cluster AnalysisCluster Analysis
Cluster Analysisguest0edcaf
 
Poggi analytics - clustering - 1
Poggi   analytics - clustering - 1Poggi   analytics - clustering - 1
Poggi analytics - clustering - 1Gaston Liberman
 
Cluster spss week7
Cluster spss week7Cluster spss week7
Cluster spss week7Birat Sharma
 

Similaire à Hierarchical Clustering | Hierarchical Clustering in R |Hierarchical Clustering Example |Simplilearn (20)

Clustering on DSS
Clustering on DSSClustering on DSS
Clustering on DSS
 
Chap8 basic cluster_analysis
Chap8 basic cluster_analysisChap8 basic cluster_analysis
Chap8 basic cluster_analysis
 
Data mining Techniques
Data mining TechniquesData mining Techniques
Data mining Techniques
 
Hierarchical methods navdeep kaur newww.pptx
Hierarchical methods navdeep kaur newww.pptxHierarchical methods navdeep kaur newww.pptx
Hierarchical methods navdeep kaur newww.pptx
 
Cluster Analysis.pptx
Cluster Analysis.pptxCluster Analysis.pptx
Cluster Analysis.pptx
 
Cluster analysis
Cluster analysisCluster analysis
Cluster analysis
 
Cluster Analysis
Cluster Analysis Cluster Analysis
Cluster Analysis
 
01 Statistika Lanjut - Cluster Analysis part 1 with sound (1).pptx
01 Statistika Lanjut - Cluster Analysis  part 1 with sound (1).pptx01 Statistika Lanjut - Cluster Analysis  part 1 with sound (1).pptx
01 Statistika Lanjut - Cluster Analysis part 1 with sound (1).pptx
 
Slide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptSlide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.ppt
 
Slide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.pptSlide-TIF311-DM-10-11.ppt
Slide-TIF311-DM-10-11.ppt
 
Data mining and warehousing
Data mining and warehousingData mining and warehousing
Data mining and warehousing
 
Clustering.pptx
Clustering.pptxClustering.pptx
Clustering.pptx
 
6 clustering
6 clustering6 clustering
6 clustering
 
Cluster Analysis
Cluster AnalysisCluster Analysis
Cluster Analysis
 
Cluster Analysis
Cluster AnalysisCluster Analysis
Cluster Analysis
 
Cluster Analysis
Cluster AnalysisCluster Analysis
Cluster Analysis
 
Poggi analytics - clustering - 1
Poggi   analytics - clustering - 1Poggi   analytics - clustering - 1
Poggi analytics - clustering - 1
 
Clustering
ClusteringClustering
Clustering
 
Cluster spss week7
Cluster spss week7Cluster spss week7
Cluster spss week7
 
Clustering.pdf
Clustering.pdfClustering.pdf
Clustering.pdf
 

Plus de Simplilearn

ChatGPT in Cybersecurity
ChatGPT in CybersecurityChatGPT in Cybersecurity
ChatGPT in CybersecuritySimplilearn
 
Whatis SQL Injection.pptx
Whatis SQL Injection.pptxWhatis SQL Injection.pptx
Whatis SQL Injection.pptxSimplilearn
 
Top 5 High Paying Cloud Computing Jobs in 2023
 Top 5 High Paying Cloud Computing Jobs in 2023  Top 5 High Paying Cloud Computing Jobs in 2023
Top 5 High Paying Cloud Computing Jobs in 2023 Simplilearn
 
Types Of Cloud Jobs In 2024
Types Of Cloud Jobs In 2024Types Of Cloud Jobs In 2024
Types Of Cloud Jobs In 2024Simplilearn
 
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...Simplilearn
 
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...Simplilearn
 
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...Simplilearn
 
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...Simplilearn
 
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...Simplilearn
 
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...Simplilearn
 
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...Simplilearn
 
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...Simplilearn
 
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...Simplilearn
 
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...Simplilearn
 
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...Simplilearn
 
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...Simplilearn
 
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...Simplilearn
 
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...Simplilearn
 
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...Simplilearn
 
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...Simplilearn
 

Plus de Simplilearn (20)

ChatGPT in Cybersecurity
ChatGPT in CybersecurityChatGPT in Cybersecurity
ChatGPT in Cybersecurity
 
Whatis SQL Injection.pptx
Whatis SQL Injection.pptxWhatis SQL Injection.pptx
Whatis SQL Injection.pptx
 
Top 5 High Paying Cloud Computing Jobs in 2023
 Top 5 High Paying Cloud Computing Jobs in 2023  Top 5 High Paying Cloud Computing Jobs in 2023
Top 5 High Paying Cloud Computing Jobs in 2023
 
Types Of Cloud Jobs In 2024
Types Of Cloud Jobs In 2024Types Of Cloud Jobs In 2024
Types Of Cloud Jobs In 2024
 
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...
Top 12 AI Technologies To Learn 2024 | Top AI Technologies in 2024 | AI Trend...
 
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...
What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning...
 
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...
Top 10 Chat GPT Use Cases | ChatGPT Applications | ChatGPT Tutorial For Begin...
 
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...
React JS Vs Next JS - What's The Difference | Next JS Tutorial For Beginners ...
 
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...
Backpropagation in Neural Networks | Back Propagation Algorithm with Examples...
 
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...
How to Become a Business Analyst ?| Roadmap to Become Business Analyst | Simp...
 
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...
Career Opportunities In Artificial Intelligence 2023 | AI Job Opportunities |...
 
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...
Programming for Beginners | How to Start Coding in 2023? | Introduction to Pr...
 
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...
Best IDE for Programming in 2023 | Top 8 Programming IDE You Should Know | Si...
 
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...
React 18 Overview | React 18 New Features and Changes | React 18 Tutorial 202...
 
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...
What Is Next JS ? | Introduction to Next JS | Basics of Next JS | Next JS Tut...
 
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...
How To Become an SEO Expert In 2023 | SEO Expert Tutorial | SEO For Beginners...
 
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...
WordPress Tutorial for Beginners 2023 | What Is WordPress and How Does It Wor...
 
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...
Blogging For Beginners 2023 | How To Create A Blog | Blogging Tutorial | Simp...
 
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...
How To Start A Blog In 2023 | Pros And Cons Of Blogging | Blogging Tutorial |...
 
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...
How to Increase Website Traffic ? | 10 Ways To Increase Website Traffic in 20...
 

Dernier

Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxDenish Jangid
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxcallscotland1987
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...pradhanghanshyam7136
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17Celine George
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024Elizabeth Walsh
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17Celine George
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseAnaAcapella
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxAreebaZafar22
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxRamakrishna Reddy Bijjam
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxVishalSingh1417
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsMebane Rash
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Google Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxGoogle Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxDr. Sarita Anand
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.MaryamAhmad92
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfSherif Taha
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Association for Project Management
 
Fostering Friendships - Enhancing Social Bonds in the Classroom
Fostering Friendships - Enhancing Social Bonds  in the ClassroomFostering Friendships - Enhancing Social Bonds  in the Classroom
Fostering Friendships - Enhancing Social Bonds in the ClassroomPooky Knightsmith
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxVishalSingh1417
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 

Dernier (20)

Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptx
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Google Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxGoogle Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptx
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Fostering Friendships - Enhancing Social Bonds in the Classroom
Fostering Friendships - Enhancing Social Bonds  in the ClassroomFostering Friendships - Enhancing Social Bonds  in the Classroom
Fostering Friendships - Enhancing Social Bonds in the Classroom
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 

Hierarchical Clustering | Hierarchical Clustering in R |Hierarchical Clustering Example |Simplilearn

  • 2. What’s in it for you? What is Clustering? What is Hierarchical Clustering? How Hierarchical Clustering works? Distance Measure What is Agglomerative Clustering? What is Divisive Clustering?
  • 4. What is Clustering? I have 20 places to cover in 4 days!
  • 5. What is Clustering? How will I manage to cover all?
  • 6. What is Clustering? You can make use of clustering by grouping the data into four clusters
  • 7. What is Clustering? Each of these clusters will have places which are close by
  • 8. What is Clustering? Then each day you can visit one group and cover all places in the group
  • 10. What is Clustering? It will group places with least distance The method of dividing the objects into clusters which are similar between them and are dissimilar to the objects belonging to another cluster
  • 11. What is Clustering? It will group places with least distance The method of dividing the objects into clusters which are similar between them and are dissimilar to the objects belonging to another cluster Partial Clustering Hierarchical Clustering
  • 12. What is Clustering? It will group places with least distance The method of dividing the objects into clusters which are similar between them and are dissimilar to the objects belonging to another cluster Partial Clustering Hierarchical Clustering Agglomerative Divisive
  • 13. What is Clustering? It will group places with least distance The method of dividing the objects into clusters which are similar between them and are dissimilar to the objects belonging to another cluster Partial Clustering Hierarchical Clustering Agglomerative Divisive K-means Fuzzy C-Means
  • 14. What is Clustering? Applications of Clustering Customer Segmentation
  • 15. What is Clustering? Customer Segmentation Insurance Applications of Clustering
  • 16. What is Clustering? Insurance City Planning Applications of Clustering Customer Segmentation
  • 18. What is Hierarchical Clustering? It will group places with least distance Let’s consider that we have a set of cars and we have to group similar ones together
  • 19. What is Hierarchical Clustering? It will group places with least distance Hierarchical Clustering creates a tree like structure and group similar objects together
  • 20. What is Hierarchical Clustering? It will group places with least distance The grouping is done till we reach the last cluster
  • 21. What is Hierarchical Clustering? It will group places with least distance Hierarchical Clustering is separating data into different groups based on some measure of similarity
  • 22. Types of Hierarchical Clustering It will group places with least distance Agglomerative It is known as Bottom-up approach
  • 23. Types of Hierarchical Clustering It will group places with least distance Agglomerative Divisive It is known as Top Down approach
  • 25. What is Hierarchical Clustering? Convergence 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 Termination Grouping Measure the distance • Let’s consider we have few points on a plane
  • 26. What is Hierarchical Clustering? Convergence 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 Termination Grouping Measure the distance • Each data point is a cluster of its own
  • 27. What is Hierarchical Clustering? Convergence 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 Termination Grouping Measure the distance • Each data point is a cluster of its own • We try to find the least distance between two data points/cluster
  • 28. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 • The two nearest clusters/datapoints are merged together Termination Grouping Measure the distance
  • 29. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 • The two nearest clusters/datapoints are merged together Termination Grouping Measure the distance P2 P1 • This is represented in a tree like structure called Dendrogram
  • 30. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 • The two nearest clusters/datapoints are merged together Termination Grouping Measure the distance • This is represented in a tree like structure called Dendrogram P3P2 P1 P4
  • 31. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 P5 P6 • The two nearest clusters/datapoints are merged together Termination Grouping Measure the distance • This is represented in a tree like structure called Dendrogram P5 P6P3 P4P2 P1
  • 32. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 P5 P6 • The two nearest clusters/datapoints are merged together Termination Grouping Measure the distance • This is represented in a tree like structure called Dendrogram P5 P6P3 P4P2 P1
  • 33. What is Hierarchical Clustering? 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P3 P4 P5 P6 0 0.2 0.4 0.6 0.8 1 1.2 0 0.5 1 1.5 Y-Values P6 P3 P4 P6 • We terminate when we are left with only one clusters Termination Grouping Measure the distance P6P3P2 P1 P P5P4
  • 34. What is Hierarchical Clustering? It will group places with least distance An algorithm that builds hierarchy of clusters 0 1 2 3 4 5 6 0 2 4 6 8 Y-Values P1P2 P5 P6 P3 P4 P5 P6 P2 P1 P3 P4 ? How do we measure the distance between the data points?
  • 36. Distance Measure Distance measure will determine the similarity between two elements and it will influence the shape of the clusters
  • 37. Distance Measure Euclidean distance measure Distance measure will determine the similarity between two elements and it will influence the shape of the clusters
  • 38. Distance Measure Euclidean distance measure Squared Euclidean distance measure Distance measure will determine the similarity between two elements and it will influence the shape of the clusters
  • 39. Distance Measure Euclidean distance measure Manhattan distance measure Squared Euclidean distance measure Distance measure will determine the similarity between two elements and it will influence the shape of the clusters
  • 40. Distance Measure Euclidean distance measure Manhattan distance measure Squared Euclidean distance measure Cosine distance measure Distance measure will determine the similarity between two elements and it will influence the shape of the clusters
  • 41. Euclidean Distance Measure • The Euclidean distance is the "ordinary" straight line • It is the distance between two points in Euclidean space d=√ 𝑖=1 𝑛 ( 𝑞𝑖− )2 p q Euclidian Distance 𝑝𝑖 Option 02 Euclidean distance measure 01 Squared euclidean distance measure 02 Manhattan distance measure 03 Cosine distance measure 04
  • 42. Squared Euclidean Distance Measure The Euclidean squared distance metric uses the same equation as the Euclidean distance metric, but does not take the square root. d= 𝑖=1 𝑛 ( 𝑞𝑖− )2 𝑝𝑖 Option 02 Euclidean distance measure 01 Squared euclidean distance measure 02 Manhattan distance measure 03 Cosine distance measure 04
  • 43. Manhattan Distance Measure Option 02 Euclidean distance measure 01 Squared euclidean distance measure 02 Manhattan distance measure 03 Cosine distance measure 04 The Manhattan distance is the simple sum of the horizontal and vertical components or the distance between two points measured along axes at right angles d= 𝑖=1 𝑛 | 𝑞 𝑥− | p q Manhattan Distance 𝑝 𝑥 +|𝑞 𝑦− |𝑝 𝑦 (x,y) (x,y)
  • 44. Cosine Distance Measure Option 02 Euclidean distance measure 01 Squared euclidean distance measure 02 Manhattan distance measure 03 Cosine distance measure 04 The cosine distance similarity measures the angle between the two vectors p q Cosine Distance 𝑖=0 𝑛−1 𝑞𝑖− 𝑖=0 𝑛−1 (𝑞𝑖)2 × 𝑖=0 𝑛−1 (𝑝𝑖)2 d= 𝑝 𝑥
  • 46. What is Agglomerative Clustering? It will group places with least distance Agglomerative Clustering begins with each element as a separate cluster and merge them into larger clusters
  • 47. What is Agglomerative Clustering? It will group places with least distance There are three key questions that needs to be answered How do we represent a cluster of more than one point?
  • 48. What is Agglomerative Clustering? It will group places with least distance There are three key questions that needs to be answered How do we determine the nearness of clusters? How do we represent a cluster of more than one point?
  • 49. What is Agglomerative Clustering? It will group places with least distance There are three key questions that needs to be answered How do we represent a cluster of more than one point? How do we determine the nearness of clusters? When to stop combining clusters?
  • 50. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space
  • 51. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space ? How do we represent a cluster of more than one point?
  • 52. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space We make use of centroids which is the average of it’s points
  • 53. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space
  • 54. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5)
  • 55. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5)
  • 56. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5) (4.5,0.5)
  • 57. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5) (4.5,0.5) (1,1)
  • 58. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5) (4.5,0.5) (4.7,1.3) (1,1)
  • 59. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5) (4.5,0.5) (4.7,1.3) (1,1)
  • 60. What is Agglomerative Clustering? It will group places with least distance (1,2) (2,1) (0,0) (4,1) (5,3) (5,0) Let’s assume that we have 6 points in a Euclidean space (1.5,1.5) (4.5,0.5) (4.7,1.3) (1,1) ? When to stop combining clusters?
  • 61. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it
  • 62. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 1: Pick a number of clusters(k) upfront We decide the number of clusters required in the beginning and we terminate when we reach the value(k)
  • 63. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Possible Challenges  This only makes sense when we know about the data Approach 1: Pick a number of clusters(k) upfront We decide the number of clusters required in the beginning and we terminate when we reach the value(k)
  • 64. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion”
  • 65. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion
  • 66. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? But, how is cohesion defined?
  • 67. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? Approach 3.1: Diameter of a cluster • Diameter is the maximum distance between any pair of points in cluster
  • 68. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? Approach 3.1: Diameter of a cluster • Diameter is the maximum distance between any pair of points in cluster • We terminate when the diameter of a new cluster exceeds the threshold
  • 69. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? Approach 3.1: Radius of a cluster
  • 70. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? Approach 3.1: Radius of a cluster • Radius is the maximum distance of a point from centroid
  • 71. What is Agglomerative Clustering? It will group places with least distance There are many approaches to it Approach 2: Stop when the next merge would create a cluster with low “cohesion” We keep clustering till the next merge of clusters creates a bad cluster/low cohesion ? Approach 3.1: Radius of a cluster • Radius is the maximum distance of a point from centroid • We terminate when the diameter of a new cluster exceeds the threshold
  • 73. What is Divisive Clustering? It will group places with least distance Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 74. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points Step 2 Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 75. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • Split it into different clustersStep 2 Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 76. What is Divisive Clustering? It will group places with least distance Convergence Step 2 Step 1 • Start with a single cluster composed of all the data points • This can be done using Monothethic divisive methods • Split it into different clusters Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 77. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • Split this into different clusters • This can be done using Monothethic divisive methods Step 2 ? What is monothetic divisive method? Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 78. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • There are two ways to do this 1. Monothethic divisive methods 2. Polythetic divisive methods ? A,B,C,D,E,F • Obtain all possible splits into two clusters Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 79. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? • Obtain all possible splits into two clusters A,B,C,D,E,F C,D,E,F A,B Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 80. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • Split this into different clusters • There are two ways to do this ? • Obtain all possible splits into two clusters A,B,C,D,E,F A,D,F C,D,E,F A,B B,C,E Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 81. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • Split this into different clusters • There are two ways to do this 1. Monothethic divisive methods 2. Polythetic divisive methods ? • Obtain all possible splits into two clusters A,B,C,D,E,F A,D,F C,D,E,F A,B B,C,E Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters A,B,C D,E,F
  • 82. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • There are two ways to do this 1. Monothethic divisive methods 2. Polythetic divisive methods ? • For each split compute cluster sum of squares Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 83. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points • There are two ways to do this 1. Monothethic divisive methods 2. Polythetic divisive methods ? • For each split compute cluster sum of squares • We select the cluster with largest sum of squares Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 84. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? • Let’s assume that the sum of squared distance is largest for 3rd split A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 85. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? • We divide it into two clusters A,B,C A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 86. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? A,B,C D,E,F A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters • We divide it into two clusters
  • 87. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? A,B,C D,E,F A B,C A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters • We divide it into two clusters
  • 88. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? A,B,C D,E,F A B,C A,B,C,D,E,F A,B,C D,E,F A B,C D E,F A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters • We divide it into two clusters
  • 89. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? A,B,C D,E,F A B,C D E,F A B C A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters • We divide it into two clusters
  • 90. What is Divisive Clustering? It will group places with least distance Convergence Step 1 • Start with a single cluster composed of all the data points ? • We terminate when every data point is it’s own cluster A,B,C D,E,F A B,C D E,F A B C D E F A,B,C,D,E,F Divisive Clustering approach begins with the whole set and proceeds to divide it into smaller clusters
  • 92. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales
  • 93. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales ?Steps?
  • 94. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Import the dataset
  • 95. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Create a scatter plot • Import the dataset
  • 96. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Create a scatter plot • Import the dataset • Normalize the data
  • 97. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Create a scatter plot • Import the dataset • Normalize the data • Calculate Euclidean Distance
  • 98. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Create a scatter plot • Import the dataset • Normalize the data • Calculate Euclidean Distance • Create a dendogram
  • 99. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • Create a scatter plot • Import the dataset • Normalize the data • Calculate Euclidean Distance • Create a dendogram • Cluster into groups
  • 100. Demo: Hierarchical Clustering Problem Statement • To group petroleum companies based on their sales Steps? • output

Notes de l'éditeur

  1. Style - 01
  2. Style - 01
  3. Style - 01
  4. Style - 01
  5. Style - 01
  6. Style - 01
  7. Style - 01
  8. Style - 01
  9. Style - 01
  10. Style - 01
  11. Style - 01
  12. Style - 01
  13. Style - 01
  14. Style - 01
  15. Style - 01
  16. Style - 01
  17. Style - 01
  18. Style - 01
  19. Style - 01
  20. Style - 01
  21. Style - 01
  22. Style - 01
  23. Style - 01
  24. Style - 01
  25. Style - 01
  26. Style - 01
  27. Style - 01
  28. Style - 01
  29. Style - 01
  30. Style - 01
  31. Style - 01
  32. Style - 01
  33. Style - 01
  34. Style - 01
  35. Style - 01
  36. Style - 01
  37. Style - 01
  38. Style - 01
  39. Style - 01
  40. Style - 01
  41. Style - 01
  42. Style - 01
  43. Style - 01
  44. Style - 01
  45. Style - 01
  46. Style - 01
  47. Style - 01
  48. Style - 01
  49. Style - 01
  50. Style - 01
  51. Style - 01
  52. Style - 01
  53. Style - 01
  54. Style - 01
  55. Style - 01
  56. Style - 01
  57. Style - 01
  58. Style - 01
  59. Style - 01
  60. Style - 01
  61. Style - 01
  62. Style - 01
  63. Style - 01
  64. Style - 01
  65. Style - 01
  66. Style - 01
  67. Style - 01
  68. Style - 01
  69. Style - 01
  70. Style - 01
  71. Style - 01
  72. Style - 01
  73. Style - 01
  74. Style - 01
  75. Style - 01
  76. Style - 01
  77. Style - 01
  78. Style - 01
  79. Style - 01
  80. Style - 01
  81. Style - 01
  82. Style - 01
  83. Style - 01