Unit – III Supervised Learning: Classification
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