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PATTERN
RECOGNITION
Tutorial 2
Aly Osama
15-10-2016
Agenda
■ Rules and Attendance
■ Lab
– Lab Configuration
– Lab Tools
– Lab Experiment
■ Tutorial
– Solve Sheet 1 “ Problem 2 and 4”
■ 15 Minutes In Deep
– Estimating Probabilities
Pattern Recognition | Tutorial 2 | Aly Osama 2
1. Rules and Attendance
■ Tutorial Starts 11:00 - Ends 1:10
■ I will start at 11:05
■ Attendance at 11:08
■ Allowance Until 11:10
Pattern Recognition | Tutorial 2 | Aly Osama 3
2. Lab Configuration - Dataset
Pattern Recognition | Tutorial 2 | Aly Osama 4
Dataset
Feature 1 Feature 2 Feature 3 Feature 4 Class(Label)
2 1 3 7 1
3 2 1 2 2
41 1 44 2 1
61 3 1 5 1
14 51 5 9 2
X2X1 X3 X4 Y
2. Lab Configuration – Experiment
Pattern Recognition | Tutorial 2 | Aly Osama 5
Dataset
Training
Dataset
Testing
Dataset
75%
25%
Pattern
Recognition
Algorithm
Model
X(Feature Vector)
Calculate
Error
Y
(Real Class)
Accuracy
Y
(Predicted Class)
2. Lab Configuration – Algorithm
Pattern Recognition | Tutorial 2 | Aly Osama 6
Pattern
Recognition
Algorithm
As Example
Naive Bayes Classifier
Assign x to W2 if :
Given
• X: given data
• W1,W2 Two classes
2. Lab Configuration – Gaussian Bayes Classifier
Pattern Recognition | Tutorial 2 | Aly Osama 7
Unknown
• Mean of Data
• Standard Deviation
Loss Matrix Probability of Classes
Given
Ex: Gaussian
Unknown
Calculated from your dataset
2. Lab Configuration – Bayes Experiment
Pattern Recognition | Tutorial 2 | Aly Osama 8
Dataset
Training
Dataset
Testing
Dataset
75%
25%
Bayes Classifier
1. Probability
2. Expectation
3. Standard
Deviation
Model
X(Feature Vector)
Calculate
Error
Y
(Real Class)
Accuracy
Y
(Predicted Class)
2.2. Lab Tools
1. Select Dataset from UCI Machine Learning Repo
– https://archive.ics.uci.edu/ml/index.html
2. Install Matlab with PR Toolbox or Python with Scikit-learn
– PR Toolbox :
■ https://drive.google.com/drive/folders/0B9lOqlIVVRRIOF9VVFBtNHU4bEk?usp=drive_web
– Scikit Learn :
■ http://scikit-learn.org/
Pattern Recognition | Tutorial 2 | Aly Osama 9
We will tell you What to do
But you have to know How to do it
Pattern Recognition | Tutorial 2 | Aly Osama 10
Time to code!
2.3. Lab Experiment
Pattern Recognition | Tutorial 2 | Aly Osama 11
15 Minutes
Time to code!
3. Tutorial
Pattern Recognition | Tutorial 2 | Aly Osama 12
1 Hour
3. Tutorial – Problem 2
Pattern Recognition | Tutorial 2 | Aly Osama 13
3. Tutorial – Solution 2
Pattern Recognition | Tutorial 2 | Aly Osama 14
3. Tutorial – Solution 2
Pattern Recognition | Tutorial 2 | Aly Osama 15
3. Tutorial – Solution 2
Pattern Recognition | Tutorial 2 | Aly Osama 16
3. Tutorial – Problem 4
Pattern Recognition | Tutorial 2 | Aly Osama 17
3. Tutorial – Solution 4
Pattern Recognition | Tutorial 2 | Aly Osama 18
3. Tutorial – Solution 4
Pattern Recognition | Tutorial 2 | Aly Osama 19
4. 15 Minutes In Deep
Pattern Recognition | Tutorial 2 | Aly Osama 20
Estimating Probabilities
???
Tasks 3
1. Quick Presentation ( 2 Minutes )
2. Try to run different random/un random splits for ( Training and Testing ) datasets
1. 75%, 25%
2. 60%, 30%
3. 50%, 50 %
3. Perform Gaussian Bayes Classifier
4. Compare your results – Report -
Pattern Recognition | Tutorial 2 | Aly Osama 21
Due date 22-10-2016
References
■ Pattern Classification, 2nd Edition Duda & Hart
■ Machine Learning, Tom Mitchell: Estimating Probabilities
Pattern Recognition | Tutorial 2 | Aly Osama 22
Pattern Recognition | Tutorial 2 | Aly Osama 23
alyosamah@gmail.com

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Pattern recognition Tutorial 2

  • 2. Agenda ■ Rules and Attendance ■ Lab – Lab Configuration – Lab Tools – Lab Experiment ■ Tutorial – Solve Sheet 1 “ Problem 2 and 4” ■ 15 Minutes In Deep – Estimating Probabilities Pattern Recognition | Tutorial 2 | Aly Osama 2
  • 3. 1. Rules and Attendance ■ Tutorial Starts 11:00 - Ends 1:10 ■ I will start at 11:05 ■ Attendance at 11:08 ■ Allowance Until 11:10 Pattern Recognition | Tutorial 2 | Aly Osama 3
  • 4. 2. Lab Configuration - Dataset Pattern Recognition | Tutorial 2 | Aly Osama 4 Dataset Feature 1 Feature 2 Feature 3 Feature 4 Class(Label) 2 1 3 7 1 3 2 1 2 2 41 1 44 2 1 61 3 1 5 1 14 51 5 9 2 X2X1 X3 X4 Y
  • 5. 2. Lab Configuration – Experiment Pattern Recognition | Tutorial 2 | Aly Osama 5 Dataset Training Dataset Testing Dataset 75% 25% Pattern Recognition Algorithm Model X(Feature Vector) Calculate Error Y (Real Class) Accuracy Y (Predicted Class)
  • 6. 2. Lab Configuration – Algorithm Pattern Recognition | Tutorial 2 | Aly Osama 6 Pattern Recognition Algorithm As Example Naive Bayes Classifier Assign x to W2 if : Given • X: given data • W1,W2 Two classes
  • 7. 2. Lab Configuration – Gaussian Bayes Classifier Pattern Recognition | Tutorial 2 | Aly Osama 7 Unknown • Mean of Data • Standard Deviation Loss Matrix Probability of Classes Given Ex: Gaussian Unknown Calculated from your dataset
  • 8. 2. Lab Configuration – Bayes Experiment Pattern Recognition | Tutorial 2 | Aly Osama 8 Dataset Training Dataset Testing Dataset 75% 25% Bayes Classifier 1. Probability 2. Expectation 3. Standard Deviation Model X(Feature Vector) Calculate Error Y (Real Class) Accuracy Y (Predicted Class)
  • 9. 2.2. Lab Tools 1. Select Dataset from UCI Machine Learning Repo – https://archive.ics.uci.edu/ml/index.html 2. Install Matlab with PR Toolbox or Python with Scikit-learn – PR Toolbox : ■ https://drive.google.com/drive/folders/0B9lOqlIVVRRIOF9VVFBtNHU4bEk?usp=drive_web – Scikit Learn : ■ http://scikit-learn.org/ Pattern Recognition | Tutorial 2 | Aly Osama 9 We will tell you What to do But you have to know How to do it
  • 10. Pattern Recognition | Tutorial 2 | Aly Osama 10 Time to code!
  • 11. 2.3. Lab Experiment Pattern Recognition | Tutorial 2 | Aly Osama 11 15 Minutes Time to code!
  • 12. 3. Tutorial Pattern Recognition | Tutorial 2 | Aly Osama 12 1 Hour
  • 13. 3. Tutorial – Problem 2 Pattern Recognition | Tutorial 2 | Aly Osama 13
  • 14. 3. Tutorial – Solution 2 Pattern Recognition | Tutorial 2 | Aly Osama 14
  • 15. 3. Tutorial – Solution 2 Pattern Recognition | Tutorial 2 | Aly Osama 15
  • 16. 3. Tutorial – Solution 2 Pattern Recognition | Tutorial 2 | Aly Osama 16
  • 17. 3. Tutorial – Problem 4 Pattern Recognition | Tutorial 2 | Aly Osama 17
  • 18. 3. Tutorial – Solution 4 Pattern Recognition | Tutorial 2 | Aly Osama 18
  • 19. 3. Tutorial – Solution 4 Pattern Recognition | Tutorial 2 | Aly Osama 19
  • 20. 4. 15 Minutes In Deep Pattern Recognition | Tutorial 2 | Aly Osama 20 Estimating Probabilities ???
  • 21. Tasks 3 1. Quick Presentation ( 2 Minutes ) 2. Try to run different random/un random splits for ( Training and Testing ) datasets 1. 75%, 25% 2. 60%, 30% 3. 50%, 50 % 3. Perform Gaussian Bayes Classifier 4. Compare your results – Report - Pattern Recognition | Tutorial 2 | Aly Osama 21 Due date 22-10-2016
  • 22. References ■ Pattern Classification, 2nd Edition Duda & Hart ■ Machine Learning, Tom Mitchell: Estimating Probabilities Pattern Recognition | Tutorial 2 | Aly Osama 22
  • 23. Pattern Recognition | Tutorial 2 | Aly Osama 23 alyosamah@gmail.com