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Functions102 in github.com/Leputa/Machine-Learning-Foundations-Techniques

⨍ Functions 102◇ Types & classes 14
↓ 12 callersMethodget0_1Error
(self,dataSet)
Regularized Linear Regression/Regularized_Linear_Regression.py:45
↓ 6 callersMethodfile2matrix
(self,filename)
Logistic Regression/Logistic Regression.py:11
↓ 6 callersMethoditeration
(self,trainingSet,lamb)
Regularized Linear Regression/Regularized_Linear_Regression.py:24
↓ 4 callersMethodKNNError
(self,trainingSet,testingSet,k=5)
KNN/K Nearest Neighbor.py:15
↓ 4 callersMethodcalError
(self,dataSet,RF,RFDS)
Decision Tree/CART.py:141
↓ 4 callersMethodtrain
(self,dataSet,level,M,r,eta,T=50000)
Backprop Neural Network/Neural Network.py:45
↓ 4 callersMethodvalidation
(self,dataSet,W,level,M)
Backprop Neural Network/Neural Network.py:54
↓ 3 callersMethodbinSplitDataSet
(self,dataSet,feature,value)
Decision Tree/CART.py:19
↓ 3 callersMethodcalculateError
(self,dataSet,s,theta,k,u)
AdaBoost Stump Algorithm/AdaBoosting.py:73
↓ 3 callersMethodcalculateError
(self,dataSet,s,theta)
Decision Stump Algorithm/ODSA.py:55
↓ 3 callersMethodcalculateError
(self,dataSet,s,theta,k,m)
Decision Stump Algorithm/DSA.py:60
↓ 3 callersMethodfile2matrix
(self,filename,target)
Support Vector Machine/Support_Vector_Machine.py:5
↓ 3 callersMethodfile2matrix
(self,filename)
Regularized Linear Regression/Regularized_Linear_Regression.py:8
↓ 3 callersMethodget0_1Error
(self,testingSet)
Logistic Regression/Logistic Regression.py:49
↓ 3 callersMethodvalidation
(self,TrainingSet,TestingSet,number)
Pocket Algorithm/PA.py:53
↓ 2 callersMethodGini
(self,dataSet)
Decision Tree/CART.py:50
↓ 2 callersMethodIteration
(self,trainingSet,a)
Logistic Regression/Logistic Regression.py:45
↓ 2 callersMethodKMeans
(self,dataSet,k,T=5000)
K-Means/K-Means.py:17
↓ 2 callersMethodbootStrapping
(self,trainingSet,m)
Decision Tree/CART.py:134
↓ 2 callersMethodcalError
(self,dataSet,K,S,k)
K-Means/K-Means.py:36
↓ 2 callersMethodcalError
(self,dataSet,dtree)
Decision Tree/CART.py:84
↓ 2 callersMethodcalculateGError
(self,dataSet,alpha,theta,s,dimension,u,iterations=300)
AdaBoost Stump Algorithm/AdaBoosting.py:80
↓ 2 callersMethodchooseBestToSplit
(self,trainingSet)
Decision Tree/CART.py:24
↓ 2 callersMethodclassfy
(self,dataSet,isFifteen)
Perception Learning Algorithm/PLA.py:24
↓ 2 callersMethodconstruct
(self,dataSet,level,M,r)
Backprop Neural Network/Neural Network.py:62
↓ 2 callersMethodcreateTree
(self,trainingSet)
Decision Tree/CART.py:60
↓ 2 callersMethodfile2matrix
(self,filename)
Backprop Neural Network/Neural Network.py:6
↓ 2 callersMethodfile2matrix
(self,filename,iterations=300)
AdaBoost Stump Algorithm/AdaBoosting.py:5
↓ 2 callersMethodfile2matrix
(self,filename)
KNN/K Nearest Neighbor.py:4
↓ 2 callersMethodfile2matrix
(self,filename)
Pocket Algorithm/PA.py:5
↓ 2 callersMethodfile2matrix
(self)
Decision Stump Algorithm/ODSA.py:11
↓ 2 callersMethodfile2matrix
(self,filename)
Decision Stump Algorithm/DSA.py:8
↓ 2 callersMethodfile2matrix
(self,filename)
Decision Tree/CART.py:7
↓ 2 callersMethodgetError
(self,belta,trainingSet,dataSet,gamma)
Kernel Ridge Regression Algorithm/LSSVM.py:48
↓ 2 callersMethodgetErrorRate
(self,dataSet,w,m)
Pocket Algorithm/PA.py:46
↓ 2 callersMethodgetGradient
(self,trainingSet)
Logistic Regression/Logistic Regression.py:27
↓ 2 callersMethodinference
(self,X,Y,W,level)
Backprop Neural Network/Neural Network.py:23
↓ 2 callersMethodkernerTrans
(self,X,x,gamma)
Kernel Ridge Regression Algorithm/LSSVM.py:33
↓ 2 callersMethodtanh
(self,s)
Backprop Neural Network/Neural Network.py:17
↓ 1 callersMethodAverageIteration
(self,dataSet,number)
Perception Learning Algorithm/PLA.py:63
↓ 1 callersMethodE_in
(self)
Decision Stump Algorithm/ODSA.py:26
↓ 1 callersMethodE_in
(self,trainingSet)
Decision Stump Algorithm/DSA.py:24
↓ 1 callersMethodE_out
(self)
Decision Stump Algorithm/ODSA.py:51
↓ 1 callersMethodE_out
(self,Testingfile)
Decision Stump Algorithm/DSA.py:51
↓ 1 callersMethodGaussianKernel
(self,trainingSet,testingSet,C)
Support Vector Machine/Support_Vector_Machine.py:57
↓ 1 callersMethodRBFkernel
(self,dataSet,gamma)
Kernel Ridge Regression Algorithm/LSSVM.py:25
↓ 1 callersFunctionRFevarageError
(trainingSet,testingSet,iteration)
Decision Tree/CART.py:160
↓ 1 callersFunctionRFevarageErrorByPrune
(trainingSet,testingSet,iteration)
Decision Tree/CART.py:174
↓ 1 callersMethodV_fold_cross_validation
(self,dataSet,v,lamb)
Regularized Linear Regression/Regularized_Linear_Regression.py:60
↓ 1 callersMethodaddNoise
(self,dataSet)
Decision Stump Algorithm/ODSA.py:19
↓ 1 callersMethodbackprop
(self,X,Y,W,S,level,eta)
Backprop Neural Network/Neural Network.py:35
↓ 1 callersMethodcalErrorDFS
(self,data,dtree)
Decision Tree/CART.py:94
↓ 1 callersMethodcalculateAverage
(self)
Decision Stump Algorithm/ODSA.py:62
↓ 1 callersMethodclassfy
(self,dataSet,eta,number)
Pocket Algorithm/PA.py:22
↓ 1 callersMethodclassfy_a
(self,dataSet,a)
Perception Learning Algorithm/PLA.py:47
↓ 1 callersMethodcomputeGini
(self,trainingSet,subDataSet0,subDataSet1)
Decision Tree/CART.py:42
↓ 1 callersMethodcreateForest
(self,trainingSet,T)
Decision Tree/CART.py:110
↓ 1 callersMethodcreatePruneForest
(self,trainingSet,T)
Decision Tree/CART.py:122
↓ 1 callersMethodcreatePruneTree
(self,trainingSet)
Decision Tree/CART.py:72
↓ 1 callersMethodcrossValidation
(self,trainingSet,C)
Support Vector Machine/Support_Vector_Machine.py:77
↓ 1 callersMethodfile2matrix
(self,filename)
Perception Learning Algorithm/PLA.py:7
↓ 1 callersMethodfile2matrix
(self,filename)
K-Means/K-Means.py:6
↓ 1 callersMethodfile2matrix
(self,filename)
Kernel Ridge Regression Algorithm/LSSVM.py:4
↓ 1 callersFunctiongetBestEta
(trainingSet,testingSet,nn)
Backprop Neural Network/Neural Network.py:123
↓ 1 callersFunctiongetBestM
(trainingSet,testingSet,nn)
Backprop Neural Network/Neural Network.py:80
↓ 1 callersFunctiongetBestR
(trainingSet,testingSet,nn)
Backprop Neural Network/Neural Network.py:102
↓ 1 callersFunctionkernelfunc
(x1,x2)
Support Vector Machine/Question2.py:7
↓ 1 callersMethodlinearKernel
(self,trainingSet,C)
Support Vector Machine/Support_Vector_Machine.py:23
↓ 1 callersFunctionmain
()
Backprop Neural Network/Neural Network.py:144
↓ 1 callersFunctionmain
()
Support Vector Machine/Support_Vector_Machine.py:100
↓ 1 callersFunctionmain
()
AdaBoost Stump Algorithm/AdaBoosting.py:126
↓ 1 callersFunctionmain
()
KNN/K Nearest Neighbor.py:29
↓ 1 callersFunctionmain
()
Perception Learning Algorithm/PLA.py:84
↓ 1 callersFunctionmain
()
Pocket Algorithm/PA.py:86
↓ 1 callersFunctionmain
()
Decision Stump Algorithm/ODSA.py:71
↓ 1 callersFunctionmain
()
Decision Stump Algorithm/DSA.py:69
↓ 1 callersFunctionmain
()
Regularized Linear Regression/Regularized_Linear_Regression.py:74
↓ 1 callersFunctionmain
()
K-Means/K-Means.py:57
↓ 1 callersFunctionmain
()
Logistic Regression/Logistic Regression.py:57
↓ 1 callersFunctionmain
()
Kernel Ridge Regression Algorithm/LSSVM.py:86
↓ 1 callersFunctionmain
()
Decision Tree/CART.py:186
↓ 1 callersMethodpolynomialKernel
(self,filename,C,Q)
Support Vector Machine/Support_Vector_Machine.py:33
↓ 1 callersMethodprint12
(self,Ein)
AdaBoost Stump Algorithm/AdaBoosting.py:91
↓ 1 callersMethodprint13
(self,u)
AdaBoost Stump Algorithm/AdaBoosting.py:98
↓ 1 callersMethodprint15
(self,u)
AdaBoost Stump Algorithm/AdaBoosting.py:105
↓ 1 callersMethodprint16
(self,minE)
AdaBoost Stump Algorithm/AdaBoosting.py:112
↓ 1 callersMethodrandomPickK
(self,dataSet,k)
K-Means/K-Means.py:45
↓ 1 callersMethodridgeRegression
(self,K,trainingSet,lamda)
Kernel Ridge Regression Algorithm/LSSVM.py:42
↓ 1 callersMethodslipDateSet
(self,dataSet)
Regularized Linear Regression/Regularized_Linear_Regression.py:53
↓ 1 callersMethodstochasticGradientDescent
(self,trainingSet,a)
Logistic Regression/Logistic Regression.py:35
↓ 1 callersMethodtanhOfDeriv
(self,s)
Backprop Neural Network/Neural Network.py:20
↓ 1 callersMethodtestError
(self,trainingSet,testingSet)
Kernel Ridge Regression Algorithm/LSSVM.py:60
↓ 1 callersMethodtrainAlphaOnTheFly
(self,trainingSet,u,iterations=300)
AdaBoost Stump Algorithm/AdaBoosting.py:20
↓ 1 callersMethodupdataU
(self,trainingSet,theta,s,u,i,dimension,diamond)
AdaBoost Stump Algorithm/AdaBoosting.py:66
Method__init__
(self)
Decision Stump Algorithm/ODSA.py:5
Method__init__
(self)
Decision Stump Algorithm/DSA.py:4
Method__init__
(self)
Regularized Linear Regression/Regularized_Linear_Regression.py:5
Method__init__
(self)
Logistic Regression/Logistic Regression.py:6
Method__init__
(self)
Decision Tree/CART.py:4
MethodgetEin
(self,trainingSet,lamb)
Regularized Linear Regression/Regularized_Linear_Regression.py:31
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