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Fundamental Algorithms in Data Mining: Methods and Models for Effective Learning

Explore basic methods in data mining from Professor Charles Tappert's Chapter 4, including statistical modeling like Naïve Bayes, decision tree construction with ID3 method, rule construction, association rules mining, linear regression, k-nearest neighbors, and k-means clustering. Understand how these algorithms work and analyze their applications in real-world scenarios.

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Fundamental Algorithms in Data Mining: Methods and Models for Effective Learning

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  1. Algorithms: The Basic MethodsWitten – Chapter 4 Charles Tappert Professor of Computer Science School of CSIS, Pace University

  2. 1. Inferring Rudimentary Rules1R (1-rule) Method This method tests a single attribute and creates a rule that assigns the most frequent class to that attribute

  3. 2. Statistical ModelingNaïve Bayes Method Assumes statistical independence – multiply probabilities

  4. 2. Statistical ModelingNaïve Bayes Method

  5. 3. Divide-and-Conquer:Construct Decision Trees: ID3 Method

  6. 3. Divide-and-Conquer:Construct Decision Trees: ID3 Method

  7. 3. Divide-and-Conquer:Construct Decision Trees: ID3 Method

  8. Compare: Example from Naïve Bayes Method 3. Divide-and-Conquer:Construct Decision Trees: ID3 Method

  9. 4. Covering Algorithms: Constructing Rules

  10. 5. Mining Association Rules

  11. 5. Mining Association Rules

  12. 6. Linear ModelsPrediction by linear regression

  13. 6. Linear ModelsLinear Classification via Perceptron

  14. 7. Instance-Based Learningk-nearest-neighbor method Non-parametric algorithm

  15. 8. Clustering: k-means TechniqueTop down method Specify in advance number of clusters, k Randomly choose k seed points Find the closest points to the seed points Compute the means of points closest to each seed point –> seeds for next iteration Stop when the seed points become stable

  16. 8. Clustering: k-means TechniqueTop down method

  17. Clustering: Hierarchy - DendrogramBottom up method Mary Manfredi dissertation Also, see Witten p 81, p 275-278

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