Machine-Learning

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Chapt. 2: K-Nearest Neighbors Algorithm

Code

• 1. Entry Level k-NN

• 2. Miss Helen Dating History

• 3. Digits Recognition

Chapt. 3: Decision Tree

Code

• 1. Loan Prediction

• 2. Contact Lenses

Chapt. 4: Navie Bayes

Code

• 1. Comment Filter

• 2. Spam Filter

• 3. News Catalogues

Chapt. 5: Logistic Regression

Code

• 1. Entry Level Exercise for Logistic Regression

• 2. Improved Random Gradient Ascent Algorithm

• 3. Prediction of Horse Mortality

Chapt. 6: SVM (Support Vector Machine)

Code

• 1. Simplified SMO Alogrithm

• 2. Complete SMO Alogrithm

• 3. Nonlinear SVM Alogrithm

• 4. Sklearn SVC

Chapt. 7: AdaBoost

Code

• 1. Training Process of AdaBoost Based On Decision Stump

• 2. AdaBoost on Hard Datasets

• 3. Implement AdaBoost by sklearn

• 4. ROC Curve Plot

Chapt. 8: Linear Regression

Code

• 1. Linear Regression(Ordinary LR + Locally Weighted LR)

• 2. Predicting the Age of Abalones(Ormers)

• 3. Stepwise Regression

• 4. Predicting the Price of Second Hand Lego

Chapt. 9: Regression Tree

Code

• 1. Regression Tree