Versions in this module Expand all Collapse all v0 v0.1.1 Jun 26, 2020 v0.1.0 Jun 23, 2020 Changes in this version + func AccumPlatt(c int, colSum *mat64.Vector, plattAB *mat64.Dense, plattASet *mat64.Dense, ...) + func AccumThres(c int, colSum *mat64.Vector, thresSet *mat64.Dense, thres *mat64.Dense) + func AccumTsYdata(iFold int, c int, colSum *mat64.Vector, tsYh *mat64.Dense, tsY *mat64.Dense, ...) + func AveThres(cBest int, thresSet *mat64.Dense, plattCountSet *mat64.Dense) (aveThres *mat64.Dense) + func BestHyperParameterSetByMeasure(trainMeasure *mat64.Dense, index int) (cBest int, value float64) + func BinPredByAlpha(Yh *mat64.Dense, rankCut int, outBin bool) (binYh *mat64.Dense, detectNanInf bool) + func ColMaxMin(data *mat64.Dense) + func ColScale(data *mat64.Dense, rebaData *mat64.Dense) (scaleData *mat64.Dense) + func ColStackMatrix(X *mat64.Dense, addX *mat64.Dense) (X2 *mat64.Dense) + func ComputeAccuracy(tsYdata *mat64.Dense, Yhat *mat64.Dense, isWeighted bool) (accuracy float64) + func ComputeAupr(Y *mat64.Vector, Yh *mat64.Vector, beta float64) (aupr float64, pAupr float64, maxFscore float64, optThres float64) + func ComputeF1_3(Y *mat64.Vector, Yh *mat64.Vector, thres float64) (F1 float64, tp int, fp int, fn int, tn int) + func DefaultThres(tsYdata *mat64.Dense, tsYhat *mat64.Dense) (thres *mat64.Dense) + func DistanceTopK(k int, rowIdx int, tsYhat *mat64.Dense, yProbTrain *mat64.Dense) (idxArr []int) + func EcocRun(tsXdata *mat64.Dense, tsYdata *mat64.Dense, trXdata *mat64.Dense, ...) (YhSet map[int]*mat64.Dense, colSum *mat64.Vector) + func EleCopy(data *mat64.Dense) (data2 *mat64.Dense) + func FeatureDataStack(sPriorData *mat64.Dense, tsRowName []string, trRowName []string, ...) (tsXdata1 *mat64.Dense, trXdata1 *mat64.Dense) + func Flat(Y *mat64.Dense) (vec *mat64.Vector) + func FscoreThres(tsYdata *mat64.Dense, tsYhat *mat64.Dense, beta float64, isParAuprThres bool) (thres *mat64.Dense) + func HyperParameterSet(maxDim int, lbL float64, hbL float64, nStep int) (kSet []int, sigmaFctsSet []float64, lamdaSet []float64) + func IOC_MFADecoding(nRowTsY int, rowIdx int, tsY_Prob *mat64.Dense, tsY_C *mat64.Dense, ...) (tsYhatData []float64) + func Init(resFolder string) (logFIle *os.File) + func LabelRelationship(trYdata *mat64.Dense) (posLabelRls *mat64.Dense, negLabelRls *mat64.Dense) + func MSE(trY *mat64.Vector, trYh *mat64.Vector) (mse float64) + func MaskZeroByThres(tsYhat *mat64.Dense, thresData *mat64.Dense) (tsYhat2 *mat64.Dense) + func MulEleByFloat64(value float64, M *mat64.Dense) (M2 *mat64.Dense) + func MultiLabelRecalibrate(kNN int, tsYhat *mat64.Dense, xTest *mat64.Dense, yPlattTrain *mat64.Dense, ...) (tsYhatCal *mat64.Dense) + func NetworkEnhance(network *mat64.Dense) (networkEnhanced *mat64.Dense) + func ParaCov(data *mat64.Dense, goro int) (covmat *mat64.Dense, err error) + func Platt(trYhat *mat64.Dense, trY *mat64.Dense, tsYhat *mat64.Dense, lamdaArr []float64) (tsYhh *mat64.Dense, plattAB *mat64.Dense, mseArr []float64) + func PlattChopScale(tsY *mat64.Dense, tsYhh *mat64.Dense) (maxArr []float64) + func PlattParameterEst(Yh *mat64.Vector, Y *mat64.Vector) (A float64, B float64) + func PlattScale(Yh *mat64.Vector, A float64, B float64) (Yhh []float64) + func PlattScaleSet(Yh *mat64.Dense, plattAB *mat64.Dense) (Yhh *mat64.Dense) + func PlattScaleSetPseudoLabel(tsYhat *mat64.Dense, trYdata *mat64.Dense, thres *mat64.Dense) (tsYhat2 *mat64.Dense, thres2 *mat64.Dense) + func Pop(pToSlice *[]float64) float64 + func PosSelect(tsYdata *mat64.Dense, colSum *mat64.Vector) (tsYdataFilter *mat64.Dense) + func PrintMemUsage() + func PropagateSet(network *mat64.Dense, trYdata *mat64.Dense, idIdx map[string]int, ...) (sPriorData *mat64.Dense, ind []int) + func PropagateSetWithPrior(priorData *mat64.Dense, priorGeneID map[string]int, ...) (sPriorData *mat64.Dense, ind []int) + func QuantileNorm(data *mat64.Dense, thresData *mat64.Dense, isTransThres bool) (normData *mat64.Dense, normThresData *mat64.Dense) + func RandListFromUniDist(length int, length2 int) (values []float64) + func RankPred(Yh *mat64.Dense, thres *mat64.Dense) (rankYh *mat64.Dense, rankThres *mat64.Dense) + func ReadFile(inFile string, rowName bool, colName bool) (dataR *mat64.Dense, rName []string, cName []string, err error) + func ReadIDfile(inFile string) (rName []string) + func ReadNetwork(inNetworkFile string) (network *mat64.Dense, idIdx map[string]int, idxToId map[int]string) + func ReadNetworkPropagate(trRowName []string, tsRowName []string, trYdata *mat64.Dense, ...) (tsXdata *mat64.Dense, trXdata *mat64.Dense, indAccum []int) + func ReadNetworkPropagateCV(f int, folds map[int][]int, trRowName []string, tsRowName []string, ...) (cvTrain []int, cvTest []int, trXdataCV *mat64.Dense, indAccum []int) + func RebalanceData(trYdata *mat64.Dense) (rebaData *mat64.Dense) + func RefillIndCol(tsX *mat64.Dense, ind []int) (tsX2 *mat64.Dense) + func Report(tsYdata *mat64.Dense, tsYhat *mat64.Dense, thresData *mat64.Dense, rankCut int, ...) (microF1 float64, accuracy float64, macroAupr float64, microAupr float64, ...) + func RescaleData(data *mat64.Dense, thresData *mat64.Dense) (scaleData *mat64.Dense) + func SOIS(trY *mat64.Dense, nFold int, ratio int, isOutInfo bool) (folds map[int][]int) + func SelectPlattAB(cBest int, plattASet *mat64.Dense, plattBSet *mat64.Dense, ...) (plattAB *mat64.Dense) + func Shift(pToSlice *[]string) string + func Sigmoid(x float64) (y float64) + func SigmoidMatrix(data *mat64.Dense) (scaleData *mat64.Dense) + func Single_compute(tsYdata *mat64.Dense, tsYhat *mat64.Dense, rankCut int) (microF1 float64, accuracy float64, macroAupr float64, microAupr float64) + func SoftThresScale(tsYhat *mat64.Dense, thresData *mat64.Dense) (tsYhat2 *mat64.Dense, thresData2 *mat64.Dense) + func SubSetTrain(iFold int, Y *mat64.Dense, Yh *mat64.Dense, predBinY *mat64.Dense, ...) (yPlattTrain *mat64.Dense, yPredTrain *mat64.Dense, xTrain *mat64.Dense, ...) + func TestDataPlattChopScale(tsYhh *mat64.Dense, maxArr []float64) + func TmmFilterForPlatt(inTrYhat *mat64.Vector, inTrY *mat64.Vector, lamda float64) (trYhat *mat64.Vector, trY *mat64.Vector) + func TopKprec(tsYdata *mat64.Dense, Yhat *mat64.Dense, k int) (kPrec float64) + func TrainRLS_Regress_CG(trFoldX *mat64.Dense, trFoldY *mat64.Dense, lamda float64, ...) (weights *mat64.Dense) + func TuneAndPredict(nFold int, fBetaThres float64, nK int, nKnn int, isFirst bool, isKnn bool, ...) (trainMeasureUpdated *mat64.Dense, testMeasureUpdated *mat64.Dense, ...) + func WriteFile(outFile string, data *mat64.Dense, name []string, isRowID bool) (err error) + func WriteNetwork(outFile string, data *mat64.Dense, idxToId map[int]string) (err error) + func WriteOutputFiles(isVerbose bool, resFolder string, trainMeasure *mat64.Dense, ...) + func YhPlattSetUpdate(iFold int, c int, YhPlattSetCalibrated map[int]*mat64.Dense, ...) + func Zscore(data *mat64.Dense) (scaleData *mat64.Dense) + type ByValue []kv + func (a ByValue) Len() int + func (a ByValue) Less(i, j int) bool + func (a ByValue) Swap(i, j int) + type CvFold struct + IndAccum []int + X *mat64.Dense + Y *mat64.Dense + func (f *CvFold) SetXYinNestedTraining(idxArr []int, matX *mat64.Dense, matY *mat64.Dense, indAccum []int) + type Model struct + func Train(X, y *mat64.Dense, bias float64, solverType int, c_, p, eps float64, ...) *Model + func (f *Model) Label() int + func (f *Model) W() []float64