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Data Mining Lecture Slides

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6 February 2018


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Data Mining Lecture Slides

  1. Introduction [PPT] [PDF] (last updated: 3 Feb, 2018).

  2. Data [PPT] [PDF] (last updated: 3 Feb, 2018).

  3. Classification: Basic Concepts and Techniques

    • Basic Concepts and Decision Trees [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Model Overfitting [PPT] [PDF] (last updated: 3 Feb, 2018).

  4. Classification: Alternative Techniques

    • Rule-based Classifier [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Nearest Neighbor Classifiers [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Na├»ve Bayes Classifier [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Artificial Neural Networks [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Support Vector Machine [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Ensemble Methods [PPT] [PDF] (last updated: 3 Feb, 2018).

    • Class Imbalance Problem [PPT] [PDF] (last updated: 3 Feb, 2018).

  5. Association Analysis: Basic Concepts and Algorithms [PPT] [PDF] (last updated: 3 Feb, 2018).

  6. Association Analysis: Advanced Concepts [PPT] [PDF] (last updated: 3 Feb, 2018).

  7. Cluster Analysis: Basic Concepts and Algorithms [PPT] [PDF] (last updated: 3 Feb, 2018).

  8. Cluster Analysis: Additional Issues and Algorithms [PPT] [PDF] (last updated: 3 Feb, 2018).

  9. Anomaly Detection [PPT] [PDF] (last updated: 3 Feb, 2018).

  10. Avoiding False Discoveries [PPT] [PDF] (last updated: 3 Feb, 2018).


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