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[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Course Syllabus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Course Syllabus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Course Syllabus ,[object Object],[object Object],[object Object],[object Object],[object Object]
Motivation:   “Necessity is the Mother of Invention” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Mine Data? Commercial Viewpoint ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Mine Data? Scientific Viewpoint ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What Is Data Mining? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Examples: What is (not) Data Mining? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining: Classification Schemes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Decisions in Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining Tasks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Classification: Definition ,[object Object],[object Object],[object Object],[object Object],[object Object]
Classification Example categorical categorical continuous class Training  Set Learn  Classifier Test Set Model
Classification: Application 1 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Classification: Application 2 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Classification: Application 3 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Classification: Application 4 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Classifying Galaxies Early Intermediate Late ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clustering Definition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Illustrating Clustering ,[object Object],Intracluster distances are minimized Intercluster distances are maximized
Clustering: Application 1 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clustering: Application 2 ,[object Object],[object Object],[object Object],[object Object]
Association Rule Discovery: Definition ,[object Object],[object Object],Rules Discovered: {Milk} --> {Coke} {Diaper, Milk} --> {Beer}
Association Rule Discovery: Application 1 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Association Rule Discovery: Application 2 ,[object Object],[object Object],[object Object],[object Object],[object Object]
The Sad Truth About Diapers and Beer ,[object Object]
Sequential Pattern Discovery: Definition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Regression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Deviation/Anomaly Detection ,[object Object],[object Object],[object Object],[object Object]
Data Mining and Induction Principle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Problems with Induction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hypothesis-Based vs. Exploratory-Based ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hypothesis-Based vs. Exploratory-Based ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining: A KDD Process ,[object Object],Data Cleaning Data Integration Databases Data Warehouse Knowledge Task-relevant Data Data Selection  Data Preprocessing Data Mining Pattern Evaluation
Steps of a KDD Process   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining and Business Intelligence   Increasing potential to support business decisions End User Business Analyst Data Analyst DBA Making Decisions Data Presentation Visualization Techniques Data Mining Information Discovery Data Exploration OLAP, MDA Statistical Analysis, Querying and Reporting Data Warehouses / Data Marts Data Sources Paper, Files, Information Providers, Database Systems, OLTP
Data Mining: On What Kind of Data? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining: Confluence of Multiple Disciplines   Data Mining Database  Technology Statistics Other Disciplines Information Science Machine Learning Visualization
Data Mining vs. Statistical Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining vs. DBMS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining and Data Warehousing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
An OLAM Architecture Data  Warehouse Meta Data MDDB OLAM Engine OLAP Engine User GUI API Data Cube API Database API Data cleaning Data integration Layer3 OLAP/OLAM Layer2 MDDB Layer1 Data Repository Layer4 User Interface Filtering&Integration Filtering Databases Mining query Mining result
DBMS, OLAP, and Data Mining   Who will buy a mutual fund in the next 6 months and why? What is the average income of mutual fund buyers by region by year? Who purchased mutual funds in the last 3 years? Example question Induction (Build the model, apply it to new data, get the result) Multidimensional data modeling, Aggregation, Statistics Deduction (Ask the question, verify with data) Method Insight and Prediction Analysis Information Type of result Knowledge discovery of hidden patterns and insights Summaries, trends and forecasts Extraction of detailed and summary data Task Data Mining OLAP DBMS
Example of DBMS, OLAP and Data Mining: Weather Data DBMS: no true 91 71 rainy 14 yes false 75 81 overcast 13 yes true 90 72 overcast 12 yes true 70 75 sunny 11 yes false 80 75 rainy 10 yes false 70 69 sunny 9 no false 95 72 sunny 8 yes true 65 64 overcast 7 no true 70 65 rainy 6 yes false 80 68 rainy 5 yes false 96 70 rainy 4 yes false 86 83 overcast 3 no true 90 80 sunny 2 no false 85 85 sunny 1 play windy humidity temperature outlook Day
Example of DBMS, OLAP and Data Mining: Weather Data ,[object Object],[object Object],[object Object],[object Object],[object Object]
Example of DBMS, OLAP and Data Mining: Weather Data ,[object Object],[object Object],[object Object],2 / 0 1 / 1 2 / 1 Week 2 2 / 0 2 / 1 0 / 2 Week 1 overcast rainy sunny 9 / 5
Example of DBMS, OLAP and Data Mining: Weather Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Major Issues in Data Warehousing and Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Major Issues in Data Warehousing and Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Data Mining

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  • 37. Data Mining and Business Intelligence Increasing potential to support business decisions End User Business Analyst Data Analyst DBA Making Decisions Data Presentation Visualization Techniques Data Mining Information Discovery Data Exploration OLAP, MDA Statistical Analysis, Querying and Reporting Data Warehouses / Data Marts Data Sources Paper, Files, Information Providers, Database Systems, OLTP
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  • 39. Data Mining: Confluence of Multiple Disciplines Data Mining Database Technology Statistics Other Disciplines Information Science Machine Learning Visualization
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  • 43. An OLAM Architecture Data Warehouse Meta Data MDDB OLAM Engine OLAP Engine User GUI API Data Cube API Database API Data cleaning Data integration Layer3 OLAP/OLAM Layer2 MDDB Layer1 Data Repository Layer4 User Interface Filtering&Integration Filtering Databases Mining query Mining result
  • 44. DBMS, OLAP, and Data Mining Who will buy a mutual fund in the next 6 months and why? What is the average income of mutual fund buyers by region by year? Who purchased mutual funds in the last 3 years? Example question Induction (Build the model, apply it to new data, get the result) Multidimensional data modeling, Aggregation, Statistics Deduction (Ask the question, verify with data) Method Insight and Prediction Analysis Information Type of result Knowledge discovery of hidden patterns and insights Summaries, trends and forecasts Extraction of detailed and summary data Task Data Mining OLAP DBMS
  • 45. Example of DBMS, OLAP and Data Mining: Weather Data DBMS: no true 91 71 rainy 14 yes false 75 81 overcast 13 yes true 90 72 overcast 12 yes true 70 75 sunny 11 yes false 80 75 rainy 10 yes false 70 69 sunny 9 no false 95 72 sunny 8 yes true 65 64 overcast 7 no true 70 65 rainy 6 yes false 80 68 rainy 5 yes false 96 70 rainy 4 yes false 86 83 overcast 3 no true 90 80 sunny 2 no false 85 85 sunny 1 play windy humidity temperature outlook Day
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