data mining

1. 19CS5251- DATA MINING
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Data Mining

2. UNIT I: DATA MINING
1.1 Motivation
1.2 Steps in Data Mining
1.3 Architecture
1.4 Data Mining and Databases
1.5 Data Warehouses
1.6 Data Mining functionalities
1.7 Classification
1.8 Data Mining Primitives
1.9 Major issues
1.10 DATA PREPROCESSING:
1.10.1 Descriptive data summarization
1.10.2 Data Cleaning
1.10.3 Data integration and transformation
1.10.4 Data Reduction
1.10.5 Data discretization and concept hierarchy generation
Data Mining
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3. 3
Topics Covered
 Unit 1
 1.6 Data Mining functionalities
August 23, 2022 Data Mining

4. Data Mining deals with the discovery of
hidden Knowledge , unexpected pattern
and new rules from large data sets
4
DATA MINING
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Data Mining

5. 1.6 Data Mining functionalities
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6. 1.6 Data Mining functionalities
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7. 1.6 Data Mining functionalities
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Evolution Analysis

8. 1.6 Data Mining functionalities
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9. 1.6 Data Mining functionalities
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10. 1.6 Data Mining functionalities
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11. 1.6 Data Mining functionalities
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12. 1.6 Data Mining functionalities
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13. 1.6 Data Mining functionalities
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14. 1.6 Data Mining functionalities
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15. 1.6 Data Mining functionalities
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16. 1.6 Data Mining functionalities
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21. 1.6 Data Mining functionalities
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22. 1.6 Data Mining functionalities
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• A 2-D plot of customer data with respect to customer locations in a city,
showing three data clusters. Each cluster “center” is marked with a “+”.

24. 1.6 Data Mining functionalities
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25. 1.6 Data Mining functionalities
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Data evolution analysis describes and models regularities or trends for
objects whose behavior changes over time.
It may include
characterization, discrimination, association and correlation analysis,
classification, prediction, or clustering of timerelated data, distinct features
of such an analysis include time-series data analysis, sequence or
periodicity pattern matching, and similarity-based data analysis.
Evolution Analysis

26. THANK YOU
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27. ACTIVITY LINK
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https://forms.gle/o541rMyPR96yybYs8