Unit – III Supervised Learning: Classification

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 Unit – III Supervised Learning: Classification

1.    What is Classification

2.    General Approach to Classification

3.    K-Nearest Neighbour Algorithm

4.    Logistic Regression

5.    Decision Trees:

a.     Construction

b.    classification and regression trees

c.     example

6.    Naive Bayesian Classifier

7.    Support Vector Machines:

a.     Optimal Separation

b.    Kernels

c.     Algorithm


👉UNIT-II (A) Supervised Learning Classification Notes

👉UNIT-III (A) Supervised Learning Classification

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