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Project: MachineLearningNote (GitHub Link)

• MachineLearningNote-master
  • GradientDescent
    • README.md
    • gradientdescent.py
  • Adaboost
    • adaboostLihang.py
    • adaboostMultiDimension.py
  • LocallyWeightedLinearRegression
    • README.md
    • LOESS.py
    • ex1.txt
  • DecisionTree
    • ID3
      • data
        • MarineOrganism.csv
        • Watermelon_continuation.csv
        • Watermelon.csv
      • Method1
        • ID3.py
  • BayesianInference
    • code
      • Bayes_email.py
      • random_extract.py
    • email
      • ham
        • 19.txt
        • 7.txt
        • 2.txt
        • 12.txt
        • 11.txt
        • 16.txt
        • 13.txt
        • 8.txt
        • 1.txt
        • 6.txt
        • 22.txt
        • 9.txt
        • 10.txt
        • 20.txt
        • 18.txt
        • 5.txt
        • 14.txt
        • 15.txt
        • 17.txt
        • 23.txt
        • 25.txt
        • 21.txt
      • spam
        • 7.txt
        • 2.txt
        • 12.txt
        • 16.txt
        • 13.txt
        • 1.txt
        • 6.txt
        • 9.txt
        • 10.txt
        • 20.txt
        • 3.txt
        • 5.txt
        • 15.txt
        • 24.txt
        • 23.txt
        • 25.txt
        • 4.txt
        • 21.txt
      • test
        • ham_4.txt
        • spam_14.txt
        • spam_18.txt
        • spam_19.txt
        • spam_22.txt
        • spam_17.txt
        • ham_24.txt
        • ham_3.txt
        • spam_11.txt
        • spam_8.txt
  • KNN
    • kNN.py
    • standard_data.py
    • README.md
    • showData.py
  • SVD
    • SVD.ipynb
  • NeuralNetwork
    • sigmoid.ipynb
    • NeuralNetwork.py
    • SimpleNueralNetwork.py
    • README.md
  • LICENSE
  • MultiwayTree
    • README.md
    • Tree.py
  • Canopy
    • useCanopy.py
    • README.md
    • canopy.py
  • SinglePass
    • SinglePass.py
    • README.md
    • BPtest.txt
  • ExponentialSmoothing
    • data1.txt
    • README.md
    • Holt_Winters.py
  • README.md
  • PCA
    • demo3d.ipynb
    • README.md
    • PCA.ipynb
  • LogisticRegression
    • logisticregression_derivative.py
    • README.md
    • logisticregression.py
  • requirements.txt
  • PytorchNote
    • Basic.ipynb
  • .gitignore

MachineLearningNote

使用python实现各种机器学习算法

OS

• Windows 10
• Ubuntu 16.04
• MaxOS 10

Requirements

• Python 3
• requirement.txt

Current List

• 贝叶斯推断BayesianInference
• 预聚类Canopy
• 决策树DecisionTree
  • 待找出更好的实现方式，可能会参考《机器学习实战》一书的代码
• 指数平滑模型ExponentialSmoothing
• 梯度下降GradientDescent
• K近邻KNN
• 局部加权回归LocallyWeightedLinearRegression
• LogisticRegression
• 多叉树MultiwayTree
• 单遍聚类SinglePass
• BP神经网路NeuralNetwork
  • NeuralNetwork.py待完善。
• Adaboost
  • adaboostMultiDimension.py待完善，每次运行误差都为0.2，代码有bug，正在解决
• 主成分分析PCA
• 奇异值分解SVD

TO DO List

• SVM
• Random Forest
• Xgboost
• GBDT
• LDA
• SGD