{"repo":"wzyonggege/statistical-learning-method","free":true,"listed":false,"github":"https://github.com/wzyonggege/statistical-learning-method","clone":"git clone https://github.com/wzyonggege/statistical-learning-method.git","description":"《统计学习方法》笔记-基于Python算法实现","language":"Jupyter Notebook","stars":2176,"topics":["python","statistical-learning"],"license":"MIT","category":"dev-tools","readme_excerpt":"Statistical Learning Method 《统计学习方法》笔记——基于 Python 算法实现 This repository is an educational companion to classic statistical-learning methods. It explains the mathematics, implements the main ideas by hand in Python, and uses scikit-learn only for comparison cells that were part of the original notebooks. The 2026 revival keeps that original purpose intact: the notebooks are learning material first, and a modern runtime is a way to make that material usable again—not a reason to replace the implementations with library calls. Project history and scope The project was created on 28 December 2017 and its original development series ended on 9 January 2018. The original Chinese notes, examples, plots, and chapter order are preserved while the maintenance work adds reproducible setup, validation, and small compatibility fixes in separate pull requests. Nine chapters Chapter Topic Notebook --- --- --- 1 最小二乘法 / Least squares least sqaure method.ipynb 2 感知机 / Perceptron Iris perceptron.ipynb 3 k 近邻法 / k-nearest neighbors KNN.ipynb 4 朴素贝叶斯 / Naive Bayes GaussianNB.ipynb 5 决策树 / Decision tree DT.ipynb 6 逻辑斯谛回归 / Logistic regression LR.ipynb 7 支持向量机 / SVM support-vector-machine.ipynb 8 AdaBoost Adaboost.ipynb 9 EM 算法 / Expectation-Maximization em.ipynb Quick start The supported development range is Python 3.10–3.13. uv creates the environment from the committed lock file: The last command executes all nine notebooks that are currently compatible with modern dependencies. The validator in","default_branch":null,"files":null,"tree":[],"storefront":"/r/wzyonggege","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/wzyonggege/statistical-learning-method/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}