/Machine-Learning-Zhou_Zhihua

《机器学习》（周志华）算法实现笔记 - The notes of the book Machine Learning (author: Zhou Zhihua)

Primary LanguageJupyter Notebook

机器学习（周志华）

Machine Learning (Author: Prof. Zhou Zhihua)

This repository contains my personal notes and codes for the book of Machine Learning written by Prof. Zhou Zhihua.

Supervised Learning

  1. Linear Model from Stratch
  2. Decision Tree from Stratch
  3. Neural Networks from Stratch
  4. Support Vector Machine from Stratch
  5. Bayes Classifier from Stratch
  6. Ensemble Learning from Stratch
  7. Dimension Deduction from Stratch
  8. Feature Selection from Stratch

Unsupervised Learning

  1. Clustering from Stratch

Example Codes in Jupyter Notebook for Book Exercise

Chapter 3. Linear Model

  • Problem 3.3 - Implementation of Logistic Regression
  • Problem 3.5 - Implementation of Linear Discrimination Analysis (LDA)

Chapter 4. Decision Tree

  • Problem 4.3 - Implementation of Iterative Dichotomiser 3 (ID3) Decision Tree
  • Problem 4.4 - Implementation of CART Decision Tree with Pruning
  • Problem 4.7 - Decision Tree Implementation with Non-Recursive Approach

Chapter 5. Neural Networks

  • Problem 5.5 - Implementation of Standard and Accumulated Back-Propagation

Chapter 6. Support Vector Machine

  • Problem 6.2 - Implementation of Support Vector Machine using Kernels

Chapter 7. Bayes Classifier

  • Problem 7.3 - Implementation of Naïve Bayes Classifier using Laplacian Correction
  • Problem 7.6 - Implementation of Averaged One-Dependent Estimator (AODE) of Semi-Naïve Bayes Classifier

Chapter 8. Ensemble Learning

Chapter 9. Clustering

  • Problem 9.4 - Implementation of K-Means Algorithm
  • Problem 9.10 - Implementation of K-Mean with Automatically K Selection

Chapter 10. Dimension Deduction

  • Problem 10.1 - Implementation of K Nearest Neighbors Algorithm (KNN)

Chapter 11. Feature Selection

  • Problem 11.1 - Implementation of Relief Algorithm for Feature-Selection in Binary Classification Problem