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Data Mining 2
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Introduction to Data Mining 10 minLecture1.1
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KDD 09 minLecture1.2
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Data Pre-processing 4
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Data Pre-processing Part 1 17 minLecture2.1
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Data Pre-processing Part 2 09 minLecture2.2
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Data Visualization Part 1 11 minLecture2.3
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Data Visualization Part 2 11 minLecture2.4
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Concept Description, Mining Frequent Patterns, Associations and Correlations 2
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Apriori algorithm 12 minLecture3.1
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FP tree 15 minLecture3.2
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Classification and Prediction 3
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Naive Bayes 1 18 minLecture4.1
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Naive Bayes 2 25 minLecture4.2
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Decision Tree 24 minLecture4.3
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Cluster Analysis: 5
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K Mean 12 minLecture5.1
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K mean clustering Sum – Type 2 where K=2 23 minLecture5.2
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K Medoid 21 minLecture5.3
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Agglomerative clustering 13 minLecture5.4
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Agglomerative Adjacency Matrix 05 minLecture5.5
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Data Warehouse and Data Mining NOTES 1
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FP Tree Copy 15 minLecture6.1
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