ml

[shrubb]

OMG, I shouldn't have mentioned all these functions here

• [x] ParamGrid

TrainData

• [x] ctor
• [x] loadFromCSV
• [x] getSubVector
• [x] getLayout
• [x] getNTrainSamples
• [x] getNTestSamples
• [x] getNSamples
• [x] getNVars
• [x] getNAllVars
• [x] getSample
• [x] getSamples
• [x] getMissing
• [x] getTrainSamples
• [x] getTrainResponses
• [x] getTrainNormCatResponses
• [x] getTestResponses
• [x] getTestNormCatResponses
• [x] getResponses
• [x] getNormCatResponses
• [x] getSampleWeights
• [x] getTrainSampleWeights
• [x] getTestSampleWeights
• [x] getVarIdx
• [x] getVarType
• [x] getResponseType
• [x] getTrainSampleIdx
• [x] getTestSampleIdx
• [x] getValues
• [x] getNormCatValues
• [x] getDefaultSubstValues
• [x] getCatCount
• [x] getClassLabels
• [x] getCatOfs
• [x] getCatMap
• [x] setTrainTestSplit
• [x] setTrainTestSplitRatio
• [x] shuffleTrainTest

StatModel

• [x] getVarCount
• [x] empty
• [x] isTrained
• [x] isClassifier
• [x] train
• [x] train
• [x] calcError
• [x] predict

NormalBayesClassifier

• [x] ctor
• [x] predictProb

KNearest

• [x] ctor
• [x] getDefaultK
• [x] setDefaultK
• [x] getIsClassifier
• [x] setIsClassifier
• [x] getEmax
• [x] setEmax
• [x] getAlgorithmType
• [x] setAlgorithmType
• [x] findNearest

SVM

Kernel

• [ ] getType
• [ ] calc
  
  
• [x] ctor
• [x] getType
• [x] setType
• [x] getGamma
• [x] setGamma
• [x] getCoef0
• [x] setCoef0
• [x] getDegree
• [x] setDegree
• [x] getC
• [x] setC
• [x] getNu
• [x] setNu
• [x] getP
• [x] setP
• [x] setClassWeights
• [x] getClassWeights
• [x] setTermCriteria
• [x] getTermCriteria
• [x] getKernelType
• [x] setKernel
• [ ] setCustomKernel
• [x] trainAuto
• [x] getSupportVectors
• [x] getDecisionFunction
• [x] getDefaultGrid

EM

• [x] ctor
• [x] getClustersNumber
• [x] setClustersNumber
• [x] getCovarianceMatrixType
• [x] setCovarianceMatrixType
• [x] getTermCriteria
• [x] setTermCriteria
• [x] getWeights
• [x] getMeans
• [x] getCovs
• [x] predict2
• [x] trainEM
• [x] trainE
• [x] trainM

DTrees

• [x] Node
• [x] Split
• [x] getMaxCategories
• [x] setMaxCategories
• [x] getMaxDepth
• [x] setMaxDepth
• [x] getMinSampleCount
• [x] setMinSampleCount
• [x] getCVFolds
• [x] setCVFolds
• [x] getUseSurrogates
• [x] setUseSurrogates
• [x] getUse1SERule
• [x] setUse1SERule
• [x] getTruncatePrunedTree
• [x] setTruncatePrunedTree
• [x] getRegressionAccuracy
• [x] setRegressionAccuracy
• [x] getPriors
• [x] setPriors
• [x] getRoots
• [x] getNodes
• [x] getSplits
• [x] getSubsets

RTrees

• [x] ctor
• [x] getCalculateVarImportance
• [x] setCalculateVarImportance
• [x] getActiveVarCount
• [x] setActiveVarCount
• [x] getTermCriteria
• [x] setTermCriteria
• [x] getVarImportance

Boost

• [x] ctor
• [x] getBoostType
• [x] setBoostType
• [x] getWeakCount
• [x] setWeakCount
• [x] getWeightTrimRate
• [x] setWeightTrimRate

ANN_MLP

• [x] ctor
• [x] setTrainMethod
• [x] getTrainMethod
• [x] setActivationFunction
• [x] setLayerSizes
• [x] getLayerSizes
• [x] getTermCriteria
• [x] setTermCriteria
• [x] getBackpropWeightScale
• [x] setBackpropWeightScale
• [x] getBackpropMomentumScale
• [x] setBackpropMomentumScale
• [x] getRpropDW0
• [x] setRpropDW0
• [x] getRpropDWPlus
• [x] setRpropDWPlus
• [x] getRpropDWMinus
• [x] setRpropDWMinus
• [x] getRpropDWMin
• [x] setRpropDWMin
• [x] getRpropDWMax
• [x] setRpropDWMax
• [x] getWeights

LogisticRegression

• [x] ctor
• [x] getLearningRate
• [x] setLearningRate
• [x] getIterations
• [x] setIterations
• [x] getRegularization
• [x] setRegularization
• [x] getTrainMethod
• [x] setTrainMethod
• [x] getMiniBatchSize
• [x] setMiniBatchSize
• [x] getTermCriteria
• [x] setTermCriteria
• [x] predict
• [x] get_learnt_thetas
• [x] randMVNormal
• [x] randGaussMixture
• [x] createConcentricSpheresTestSet

[shrubb]

Setting custom kernel for SVM is a trouble :(

[soumith]

woohoo! that's nice.