机器学习入门经典算法代码

【文件属性】：
文件名称：机器学习入门经典算法代码
文件大小：39.91MB
文件格式：ZIP
更新时间：2022-05-14 03:48:12
machin 机器学习入门经典算法剖析代码以及Jupyter Notebook例子、源码阐述

【文件预览】：
Python3_machine_learning
----.ipynb_checkpoints()
----kNN()
--------.ipynb_checkpoints()
--------kNN.ipynb(1.25MB)
--------preprocessing.py(1KB)
--------metrics.py(291B)
--------kNN.py(2KB)
--------__pycache__()
--------model_selection.py(680B)
--------GridSearch.py(1KB)
----Decision Tree-DT()
--------.ipynb_checkpoints()
--------Optional-02-Model-Complexity-Curve-for-Decision-Tree.ipynb(43KB)
--------DT-GiniCoef.ipynb(629KB)
--------Optional-01-Learning-Curve-for-Decision-Tree.ipynb(145KB)
--------DT-Boundedness.ipynb(24KB)
--------DT Basic.ipynb(1.1MB)
----Gradient Descent-GD()
--------.ipynb_checkpoints()
--------my_LinearRegression.py(5KB)
--------StochasticGradientDescent.ipynb(1.08MB)
--------my_model_selection.py(680B)
--------__pycache__()
--------GD_LinearR.ipynb(1.6MB)
--------my_metrics.py(902B)
--------GD_basics.ipynb(608KB)
----Logistic Regression-LR()
--------.ipynb_checkpoints()
--------my_LogisticRegression.py(3KB)
--------LR-PF.ipynb(597KB)
--------my_model_selection.py(680B)
--------metrics.py(1KB)
--------__pycache__()
--------LR Basic.ipynb(3.11MB)
----Polynomial Regression-PR()
--------.ipynb_checkpoints()
--------Regularization.ipynb(1.78MB)
--------PR Basic.ipynb(172KB)
--------Overfitting and Underfitting.ipynb(1.04MB)
--------Cross Validation.ipynb(2.21MB)
----Ensemble Learning-EL()
--------.ipynb_checkpoints()
--------Boosting.ipynb(1.56MB)
--------EL-Bagging-Pasting.ipynb(1.2MB)
--------EL Basic.ipynb(530KB)
--------Random Forest.ipynb(281KB)
----Regression()
--------.ipynb_checkpoints()
--------Basic.ipynb(185KB)
--------my_LinearRegression.py(1KB)
--------my_model_selection.py(680B)
--------my_SimpleLinearRegression.py(3KB)
--------Estimate.ipynb(1MB)
--------__pycache__()
--------Multiple Linear Regression.ipynb(642KB)
--------my_metrics.py(902B)
----Classifier Estimate-CM()
--------.ipynb_checkpoints()
--------ConfusionMatrix.ipynb(1.49MB)
--------__pycache__()
--------my_metrics.py(2KB)
----__pycache__()
--------kNN.cpython-37.pyc(3KB)
----Principal Component Analysis-PCA()
--------PrincipalComponentAnalysis Basic.ipynb(2.04MB)
--------.ipynb_checkpoints()
--------PCA NoiseReduction.ipynb(112KB)
--------MNIST.ipynb(6KB)
--------Eigenface.ipynb(694KB)
--------__pycache__()
--------my_PCA.py(2KB)
----Support Vector Machine-SVM()
--------.ipynb_checkpoints()
--------SVM Basic.ipynb(2.02MB)
--------SVM-PF-GaussianKernel.ipynb(1.15MB)
--------SVM-Regression.ipynb(3KB)