文件名称：Statistical-Learning-Method_Code.zip
文件大小：30.94MB
文件格式：ZIP
更新时间：2024-03-14 10:55:51
static_learning
Statistical-Learning-Method_Code demo
【文件预览】：
Statistical-Learning-Method_Code
----PLSA()
--------PLSA.py(8KB)
--------PLSA.ipynb(10KB)
--------bbc_text.csv(4.82MB)
----Clustering()
--------Hierachical_Clustering()
--------iris.data(4KB)
--------K-means_Clustering()
----Page_Rank()
--------Page_Rank.ipynb(5KB)
--------directed_graph.png(49KB)
--------Page_Rank.py(4KB)
----LDA()
--------LDA.py(9KB)
--------bbc_text.csv(4.82MB)
--------LDA.ipynb(12KB)
----AdaBoost()
--------AdaBoost.py(11KB)
----PCA()
--------PCA.ipynb(10KB)
--------cars.csv(29KB)
--------PCA.py(4KB)
----perceptron()
--------perceptron_dichotomy.py(6KB)
----transMnist()
--------transMnist.py(1KB)
--------Mnist()
----SVM()
--------SVM.py(19KB)
----EM()
--------EM.py(7KB)
----CodePic.png(21KB)
----DecisionTree()
--------DecisionTree.py(15KB)
----NaiveBayes()
--------NaiveBayes.py(9KB)
----README.md(5KB)
----Logistic_and_maximum_entropy_models()
--------logisticRegression.py(6KB)
--------maxEntropy.py(12KB)
----KNN()
--------KNN.py(7KB)
----HMM()
--------HMM.py(18KB)
--------testArtical.txt(3KB)
--------HMMTrainSet.txt(7.37MB)
----LSA()
--------LSA.py(5KB)
--------LSA.ipynb(7KB)
--------bbc_text.csv(4.82MB)
----Mnist()
--------mnist_test.rar(1.86MB)
--------mnist_train.rar(11.18MB)