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analytics
analytics#nmf(mat, k[, json])
analytics~ActiveLearnerParam
analytics~BiasedGkParam
analytics~BufferedDigestParam
analytics~detectorParam
analytics~DpMeansExplain
analytics~DpMeansParam
analytics~GkParam

analytics~hazardModelParam
analytics~KMeansExplain
analytics~KMeansParam
analytics~logisticRegParam
analytics~MDSParam
analytics~NearestNeighborADExplain
analytics~NearestNeighborADFeatureContribution
analytics~nnetParam
analytics~oneVsAllParam

analytics~PCAParam
analytics~recLinRegParam
analytics~RecSysParam
analytics~ridgeRegParam
analytics~SVMParam
analytics~TDigestParam
analytics~tokenizerParam

analytics.BiasedGk

analytics.BiasedGk([arg])
analytics.BiasedGk.compress(val)
analytics.BiasedGk.init

analytics.BiasedGk.memory
analytics.BiasedGk.samples
analytics.BiasedGk.save(fout)

analytics.BiasedGk.size
analytics.BiasedGk#getParams()
analytics.BiasedGk#quantile(pVals)

analytics.BufferedTDigest

analytics.BufferedTDigest([arg])
analytics.BufferedTDigest.memory
analytics.BufferedTDigest.size

analytics.BufferedTDigest#flush()
analytics.BufferedTDigest#getParams()
analytics.BufferedTDigest#init

analytics.BufferedTDigest#insert(x)
analytics.BufferedTDigest#quantile(x)
analytics.BufferedTDigest#save(fout)

analytics.DpMeans

analytics.DpMeans([arg])
analytics.DpMeans#centroids
analytics.DpMeans#explain(X)
analytics.DpMeans#explain~featureContrib(x, y)
analytics.DpMeans#fit(X)

analytics.DpMeans#getModel()
analytics.DpMeans#getParams()
analytics.DpMeans#idxv
analytics.DpMeans#medoids
analytics.DpMeans#permuteCentroids(mapping)

analytics.DpMeans#predict(A)
analytics.DpMeans#relMeanCentroidDist
analytics.DpMeans#save(fout)
analytics.DpMeans#setParams(params)
analytics.DpMeans#transform(A)

analytics.Gk

analytics.Gk([arg])
analytics.Gk.compress(val)
analytics.Gk.init
analytics.Gk.kolmogorovStat(distribution)

analytics.Gk.kolmogorovTest(distribution, alpha)
analytics.Gk.memory
analytics.Gk.samples
analytics.Gk.save(fout)

analytics.Gk.size
analytics.Gk#cdf(vals)
analytics.Gk#getParams()
analytics.Gk#quantile(pVals)

analytics.KMeans

analytics.KMeans([arg])
analytics.KMeans#centroids
analytics.KMeans#explain(X)
analytics.KMeans#explain~featureContrib(x, y)
analytics.KMeans#fit(X)

analytics.KMeans#getModel()
analytics.KMeans#getParams()
analytics.KMeans#idxv
analytics.KMeans#medoids
analytics.KMeans#permuteCentroids(mapping)

analytics.KMeans#predict(A)
analytics.KMeans#relMeanCentroidDist
analytics.KMeans#save(fout)
analytics.KMeans#setParams(params)
analytics.KMeans#transform(A)

analytics.LogReg

analytics.LogReg([arg])
analytics.LogReg#fit(X, y[, eps])
analytics.LogReg#getParams()

analytics.LogReg#predict(x)
analytics.LogReg#save(fout)
analytics.LogReg#setParams(param)

analytics.LogReg#weights

analytics.MDS

analytics.MDS([arg])
analytics.MDS#fitTransform(mat[, callback])

analytics.MDS#getParams()
analytics.MDS#save(fout)

analytics.MDS#setParams(params)

analytics.NNet

analytics.NNet([arg])
analytics.NNet#fit(X, Y)

analytics.NNet#getParams()
analytics.NNet#predict(vec)

analytics.NNet#save(fout)
analytics.NNet#setParams()

analytics.NearestNeighborAD

analytics.NearestNeighborAD([arg])
analytics.NearestNeighborAD#decisionFunction(x)
analytics.NearestNeighborAD#explain(x)
analytics.NearestNeighborAD#fit(A[, idVec])

analytics.NearestNeighborAD#getModel()
analytics.NearestNeighborAD#getParams()
analytics.NearestNeighborAD#init
analytics.NearestNeighborAD#partialFit(X, recId)

analytics.NearestNeighborAD#predict(x)
analytics.NearestNeighborAD#save(fout)
analytics.NearestNeighborAD#setParams(params)

analytics.OneVsAll

analytics.OneVsAll([arg])
analytics.OneVsAll#decisionFunction(X)

analytics.OneVsAll#fit(X, y)
analytics.OneVsAll#getParams()

analytics.OneVsAll#predict(X)
analytics.OneVsAll#setParams(params)

analytics.PCA

analytics.PCA([arg])
analytics.PCA#fit(A)
analytics.PCA#getModel()

analytics.PCA#getParams()
analytics.PCA#inverseTransform(x)
analytics.PCA#save(fout)

analytics.PCA#setParams(param)
analytics.PCA#transform(x)

analytics.PropHazards

analytics.PropHazards([arg])
analytics.PropHazards#fit(X, y[, eps])
analytics.PropHazards#getParams()

analytics.PropHazards#predict(x)
analytics.PropHazards#save(fout)
analytics.PropHazards#setParams(params)

analytics.PropHazards#weights

analytics.RecLinReg

analytics.RecLinReg(arg)
analytics.RecLinReg#dim
analytics.RecLinReg#fit(mat, vec)
analytics.RecLinReg#getModel()

analytics.RecLinReg#getParams()
analytics.RecLinReg#partialFit(vec, num)
analytics.RecLinReg#predict(vec)
analytics.RecLinReg#save(fout)

analytics.RecLinReg#setParams(params)
analytics.RecLinReg#weights

analytics.RecommenderSys

analytics.RecommenderSys([arg])
analytics.RecommenderSys#fit(A)

analytics.RecommenderSys#getModel()
analytics.RecommenderSys#getParams()

analytics.RecommenderSys#save(fout)
analytics.RecommenderSys#setParams(params)

analytics.RidgeReg

analytics.RidgeReg([arg])
analytics.RidgeReg#decisionFunction(x)
analytics.RidgeReg#fit(X, y)

analytics.RidgeReg#getModel()
analytics.RidgeReg#getParams()
analytics.RidgeReg#predict(x)

analytics.RidgeReg#save(fout)
analytics.RidgeReg#setParams(gamma)
analytics.RidgeReg#weights

analytics.SVC

analytics.SVC([arg])
analytics.SVC#decisionFunction(X)
analytics.SVC#fit(X, y)

analytics.SVC#getModel()
analytics.SVC#getParams()
analytics.SVC#predict(X)

analytics.SVC#save(fout)
analytics.SVC#setParams(param)
analytics.SVC#weights

analytics.SVR

analytics.SVR([arg])
analytics.SVR#decisionFunction(X)
analytics.SVR#fit(X, y)

analytics.SVR#getModel()
analytics.SVR#getParams()
analytics.SVR#predict(X)

analytics.SVR#save(fout)
analytics.SVR#setParams(param)
analytics.SVR#weights

analytics.Sigmoid

analytics.Sigmoid([arg])
analytics.Sigmoid#decisionFunction(x)
analytics.Sigmoid#fit(x, y)

analytics.Sigmoid#getModel()
analytics.Sigmoid#getParams()
analytics.Sigmoid#predict(x)

analytics.Sigmoid#save(fout)
analytics.Sigmoid#setParams(arg)

analytics.TDigest

analytics.TDigest([arg])
analytics.TDigest.memory
analytics.TDigest.size

analytics.TDigest#getParams()
analytics.TDigest#init
analytics.TDigest#insert(x)

analytics.TDigest#quantile(x)
analytics.TDigest#save(fout)

analytics.ThresholdModel

analytics.ThresholdModel([arg])
analytics.ThresholdModel#decisionFunction(x)

analytics.ThresholdModel#fit(X, y)
analytics.ThresholdModel#predict(x)

analytics.Tokenizer

analytics.Tokenizer([arg])
analytics.Tokenizer#getParagraphs(str)

analytics.Tokenizer#getSentences(str)
analytics.Tokenizer#getTokens(str)

analytics~ActiveLearner

analytics~ActiveLearner([arg])
analytics~ActiveLearner#_assertLabel()
analytics~ActiveLearner#_assertLabelSet()
analytics~ActiveLearner#_assertMatrix()
analytics~ActiveLearner#_getDefaultSettings()
analytics~ActiveLearner#_getLabArr()
analytics~ActiveLearner#_getLabelMapFromArr()

analytics~ActiveLearner#_getLabIdxArr()
analytics~ActiveLearner#_getQueryIdx(X, y, SVC[, num])
analytics~ActiveLearner#_getUnlabIdxArr()
analytics~ActiveLearner#_retrain(X, y, SVC)
analytics~ActiveLearner#getQueryIdx([num])
analytics~ActiveLearner#getSVC()
analytics~ActiveLearner#getX()

analytics~ActiveLearner#gety()
analytics~ActiveLearner#load(input)
analytics~ActiveLearner#retrain()
analytics~ActiveLearner#save(output)
analytics~ActiveLearner#setLabel(idx, label)
analytics~ActiveLearner#setX(X)
analytics~ActiveLearner#sety(_y)

analytics~metrics

analytics~metrics
analytics~metrics.accuracyScore(yTrue, yPred)
analytics~metrics.bestF1Threshold(yTrue, yPred)
analytics~metrics.breakEventPointScore(yTrue, yPred)
analytics~metrics.desiredPrecisionThreshold(yTrue, yPred, desiredPrecision)
analytics~metrics.desiredRecallThreshold(yTrue, yPred, desiredRecall)

analytics~metrics.f1Score(yTrue, yPred)
analytics~metrics.meanAbsoluteError(yTrueVec, yPredVec)
analytics~metrics.meanAbsolutePercentageError(yTrueVec, yPredVec)
analytics~metrics.meanError(yTrueVec, yPredVec)
analytics~metrics.meanSquareError(yTrueVec, yPredVec)
analytics~metrics.precisionRecallCurve(yTrue, yPred[, sample])

analytics~metrics.precisionScore(yTrue, yPred)
analytics~metrics.r2Score(yTrueVec, yPredVec)
analytics~metrics.recallScore(yTrue, yPred)
analytics~metrics.rocAucScore(yTrue, yPred[, sample])
analytics~metrics.rocCurve(yTrue, yPred[, sample])
analytics~metrics.rootMeanSquareError(yTrueVec, yPredVec)

analytics~metrics.ClassificationScore

analytics~metrics.ClassificationScore(yTrue, yPred)

analytics~metrics.ClassificationScore#push(correct, predicted)

analytics~metrics.ClassificationScore#scores

analytics~metrics.MeanAbsoluteError

analytics~metrics.MeanAbsoluteError([fin])

analytics~metrics.MeanAbsolutePercentageError

analytics~metrics.MeanAbsolutePercentageError([fin])

analytics~metrics.MeanError

analytics~metrics.MeanError([fin])

analytics~metrics.MeanSquareError

analytics~metrics.MeanSquareError([fin])

analytics~metrics.PredictionCurve

analytics~metrics.PredictionCurve(yTrue, yPred)
analytics~metrics.PredictionCurve#allNegatives
analytics~metrics.PredictionCurve#allPositives
analytics~metrics.PredictionCurve#auc([sample])
analytics~metrics.PredictionCurve#bestF1()

analytics~metrics.PredictionCurve#breakEvenPoint()
analytics~metrics.PredictionCurve#desiredPrecision(desiredPrecision)
analytics~metrics.PredictionCurve#desiredRecall(desiredRecall)
analytics~metrics.PredictionCurve#grounds
analytics~metrics.PredictionCurve#length

analytics~metrics.PredictionCurve#precisionRecallCurve([sample])
analytics~metrics.PredictionCurve#predictions
analytics~metrics.PredictionCurve#push(ground, predicted)
analytics~metrics.PredictionCurve#roc([sample])

analytics~metrics.R2Score

analytics~metrics.R2Score([fin])

analytics~metrics.RootMeanSquareError

analytics~metrics.RootMeanSquareError([fin])

analytics~preprocessing

analytics~preprocessing

analytics~preprocessing.applyModel(model, X)

analytics~preprocessing.Binarizer

analytics~preprocessing.Binarizer(y, positiveLabel[, positiveId][, negativeId])

analytics~preprocessing.Binarizer#transform(y)

fs

fs
fs.copy(source, dest)
fs.del(fileName)
fs.exists(fileName)
fs.fileInfo(fileName)
fs.listFile(dirName[, fileExtension][, recursive])

fs.mkdir(dirName)
fs.move(source, dest)
fs.openAppend(fileName)
fs.openRead(fileName)
fs.openWrite(fileName)
fs.readCsvLines(buffer, opts)

fs.readLines(buffer, onLine(line), onEnd(err))
fs.rename(source, dest)
fs.rmdir(dirName)
fs~FileInfo

fs.FIn

fs.FIn(fileName)
fs.FIn#close()
fs.FIn#eof
fs.FIn#getCh()

fs.FIn#isClosed()
fs.FIn#length
fs.FIn#peekCh()
fs.FIn#readAll()

fs.FIn#readJson()
fs.FIn#readLine()
fs.FIn#readString()

fs.FOut

fs.FOut(fileName[, append])
fs.FOut#close()
fs.FOut#flush()

fs.FOut#write(arg)
fs.FOut#writeBinary(str)
fs.FOut#writeJson()

fs.FOut#writeLine(str)

ht

ht

ht.IntFltMap

ht.IntFltMap()
ht.IntFltMap#dat(n)
ht.IntFltMap#get(key)
ht.IntFltMap#hasKey(key)

ht.IntFltMap#key(n)
ht.IntFltMap#keyId(key)
ht.IntFltMap#length
ht.IntFltMap#load(fin)

ht.IntFltMap#put(key, data)
ht.IntFltMap#save(fout)
ht.IntFltMap#sortDat([asc])
ht.IntFltMap#sortKey([asc])

ht.IntIntMap

ht.IntIntMap()
ht.IntIntMap#dat(n)
ht.IntIntMap#get(key)
ht.IntIntMap#hasKey(key)

ht.IntIntMap#key(n)
ht.IntIntMap#keyId(key)
ht.IntIntMap#length
ht.IntIntMap#load(fin)

ht.IntIntMap#put(key, data)
ht.IntIntMap#save(fout)
ht.IntIntMap#sortDat([asc])
ht.IntIntMap#sortKey([asc])

ht.IntStrMap

ht.IntStrMap()
ht.IntStrMap#dat(n)
ht.IntStrMap#get(key)
ht.IntStrMap#hasKey(key)

ht.IntStrMap#key(n)
ht.IntStrMap#keyId(key)
ht.IntStrMap#length
ht.IntStrMap#load(fin)

ht.IntStrMap#put(key, data)
ht.IntStrMap#save(fout)
ht.IntStrMap#sortDat([asc])
ht.IntStrMap#sortKey([asc])

ht.StrFltMap

ht.StrFltMap()
ht.StrFltMap#dat(n)
ht.StrFltMap#get(key)
ht.StrFltMap#hasKey(key)

ht.StrFltMap#key(n)
ht.StrFltMap#keyId(key)
ht.StrFltMap#length
ht.StrFltMap#load(fin)

ht.StrFltMap#put(key, data)
ht.StrFltMap#save(fout)
ht.StrFltMap#sortDat([asc])
ht.StrFltMap#sortKey([asc])

ht.StrIntMap

ht.StrIntMap()
ht.StrIntMap#dat(n)
ht.StrIntMap#get(key)
ht.StrIntMap#hasKey(key)

ht.StrIntMap#key(n)
ht.StrIntMap#keyId(key)
ht.StrIntMap#length
ht.StrIntMap#load(fin)

ht.StrIntMap#put(key, data)
ht.StrIntMap#save(fout)
ht.StrIntMap#sortDat([asc])
ht.StrIntMap#sortKey([asc])

ht.StrStrMap

ht.StrStrMap()
ht.StrStrMap#classDesc()
ht.StrStrMap#dat(n)
ht.StrStrMap#get(key)
ht.StrStrMap#hasKey(key)

ht.StrStrMap#key(n)
ht.StrStrMap#keyId(key)
ht.StrStrMap#length
ht.StrStrMap#load(fin)
ht.StrStrMap#put(key, data)

ht.StrStrMap#save(fout)
ht.StrStrMap#sortDat([asc])
ht.StrStrMap#sortKey([asc])

la

la
la.cat(nestedArrMat)
la.conjgrad(A, b[, x][, verbose])
la.copyVecToArray(vec)
la.eye(dim)
la.findMaxIdx(X)
la.inverseSVD(mat)
la.ones(dim)
la.pdist2(X1, X2)
la.randi(num[, len])
la.randn([arg1][, arg2])
la.randPerm(k)
la.randVariation(n, k)
la.rangeVec(min, max)
la.sparse(rows[, cols])
la.speye(dim)
la.square(x)
la.zeros(rows[, cols])

la#qr(mat[, tol])
la#svd(mat, k[, json][, callback])
la~boolVectorCompareCb(arg1, arg2)
la~intVectorCompareCb(arg1, arg2)
la~matrixArg
la~skip.exports.BoolVector#getMaxIdx()
la~skip.exports.BoolVector#outer(vec)
la~skip.exports.BoolVector#sort([arg])
la~skip.exports.BoolVector#sortPerm([asc])
la~skip.exports.BoolVector#spDiag()
la~skip.exports.BoolVector#subVec(arg)
la~skip.exports.BoolVector#sum()
la~skip.exports.IntVector#outer(vec)
la~skip.exports.IntVector#sort([arg])
la~skip.exports.IntVector#sortPerm([asc])
la~skip.exports.IntVector#spDiag()
la~skip.exports.StrVector#getMaxIdx()
la~skip.exports.StrVector#outer(vec)

la~skip.exports.StrVector#sort([arg])
la~skip.exports.StrVector#sortPerm([asc])
la~skip.exports.StrVector#spDiag()
la~skip.exports.StrVector#sum()
la~skip.exports.Vector#cosine(vec)
la~skip.exports.Vector#diag()
la~skip.exports.Vector#inner(vec)
la~skip.exports.Vector#minus(vec)
la~skip.exports.Vector#multiply(val)
la~skip.exports.Vector#norm()
la~skip.exports.Vector#normalize()
la~skip.exports.Vector#plus(vec)
la~skip.exports.Vector#sparse()
la~skip.exports.Vector#toMat()
la~strVectorCompareCb(arg1, arg2)
la~vectorCompareCb(arg1, arg2)

la.BoolVector

la.BoolVector([arg])
la.BoolVector#at(index)
la.BoolVector#length
la.BoolVector#load(fin)
la.BoolVector#loadascii(fin)
la.BoolVector#push(val)

la.BoolVector#pushV(vec)
la.BoolVector#put(idx, val)
la.BoolVector#save(fout)
la.BoolVector#saveascii(fout)
la.BoolVector#shuffle()
la.BoolVector#splice(start, deleteCount[, ...itemN])

la.BoolVector#toArray()
la.BoolVector#toString()
la.BoolVector#trunc(idx)
la.BoolVector#unshift(...args)

la.IntVector

la.IntVector([arg])
la.IntVector#at(index)
la.IntVector#getMaxIdx()
la.IntVector#length
la.IntVector#load(fin)
la.IntVector#loadascii(fin)
la.IntVector#push(val)

la.IntVector#pushV(vec)
la.IntVector#put(idx, val)
la.IntVector#save(fout)
la.IntVector#saveascii(fout)
la.IntVector#shuffle()
la.IntVector#splice(start, deleteCount[, ...itemN])
la.IntVector#subVec(arg)

la.IntVector#sum()
la.IntVector#toArray()
la.IntVector#toString()
la.IntVector#trunc(idx)
la.IntVector#unshift(...args)

la.Matrix

la.Matrix([arg])
la.Matrix#at(rowIdx, colIdx)
la.Matrix#colMaxIdx(colIdx)
la.Matrix#colNorms()
la.Matrix#cols
la.Matrix#diag()
la.Matrix#frob()
la.Matrix#getCol(colIdx)
la.Matrix#getColSubmatrix(intVec)
la.Matrix#getRow(rowIdx)
la.Matrix#getSubmatrix(minRow, maxRow, minCol, maxCol)

la.Matrix#load(fin)
la.Matrix#minus(mat)
la.Matrix#multiply(arg)
la.Matrix#multiplyT(arg)
la.Matrix#normalizeCols()
la.Matrix#plus(mat)
la.Matrix#print()
la.Matrix#put(rowIdx, colIdx, arg)
la.Matrix#rowMaxIdx(rowIdx)
la.Matrix#rowNorms()
la.Matrix#rows

la.Matrix#save(fout)
la.Matrix#setCol(colIdx, vec)
la.Matrix#setRow(rowIdx, vec)
la.Matrix#solve(vec)
la.Matrix#sparse()
la.Matrix#toArray()
la.Matrix#toMat()
la.Matrix#toString()
la.Matrix#transpose()

la.SparseMatrix

la.SparseMatrix([arg][, rows])
la.SparseMatrix#at(rowIdx, colIdx)
la.SparseMatrix#clear()
la.SparseMatrix#colNorms()
la.SparseMatrix#cols
la.SparseMatrix#frob()
la.SparseMatrix#frob2()
la.SparseMatrix#full()
la.SparseMatrix#getCol(colIdx)

la.SparseMatrix#getColSubmatrix(columnIdVec)
la.SparseMatrix#load(fin)
la.SparseMatrix#minus(mat)
la.SparseMatrix#multiply(arg)
la.SparseMatrix#multiplyT(arg)
la.SparseMatrix#nnz()
la.SparseMatrix#normalizeCols()
la.SparseMatrix#plus(mat)
la.SparseMatrix#print()

la.SparseMatrix#push(spVec)
la.SparseMatrix#put(rowIdx, colIdx, num)
la.SparseMatrix#rows
la.SparseMatrix#save(fout[, saveMatlab])
la.SparseMatrix#setCol(colIdx, spVec)
la.SparseMatrix#setRowDim(rowDim)
la.SparseMatrix#toString()
la.SparseMatrix#transpose()

la.SparseVector

la.SparseVector([arg][, dim])
la.SparseVector#at(idx)
la.SparseVector#dim
la.SparseVector#full()
la.SparseVector#idxVec()

la.SparseVector#inner(arg)
la.SparseVector#multiply(num)
la.SparseVector#nnz
la.SparseVector#norm()
la.SparseVector#normalize()

la.SparseVector#print()
la.SparseVector#put(idx, num)
la.SparseVector#sum()
la.SparseVector#toString()
la.SparseVector#valVec()

la.StrVector

la.StrVector([arg])
la.StrVector#at(index)
la.StrVector#length
la.StrVector#load(fin)
la.StrVector#loadascii(fin)
la.StrVector#push(val)

la.StrVector#pushV(vec)
la.StrVector#put(idx, val)
la.StrVector#save(fout)
la.StrVector#saveascii(fout)
la.StrVector#shuffle()
la.StrVector#splice(start, deleteCount[, ...itemN])

la.StrVector#subVec(arg)
la.StrVector#toArray()
la.StrVector#toString()
la.StrVector#trunc(idx)
la.StrVector#unshift(...args)

la.Vector

la.Vector([arg])
la.Vector#at(index)
la.Vector#cosine(vec)
la.Vector#diag()
la.Vector#getMaxIdx()
la.Vector#inner(vec)
la.Vector#length
la.Vector#load(fin)
la.Vector#loadascii(fin)
la.Vector#minus(vec)
la.Vector#multiply(val)
la.Vector#norm()

la.Vector#normalize()
la.Vector#outer(vec)
la.Vector#plus(vec)
la.Vector#print()
la.Vector#push(val)
la.Vector#pushV(vec)
la.Vector#put(idx, val)
la.Vector#save(fout)
la.Vector#saveascii(fout)
la.Vector#shuffle()
la.Vector#sort([arg])
la.Vector#sortPerm([asc])

la.Vector#sparse()
la.Vector#spDiag()
la.Vector#splice(start, deleteCount[, ...itemN])
la.Vector#subVec(arg)
la.Vector#sum()
la.Vector#toArray()
la.Vector#toMat()
la.Vector#toString()
la.Vector#trunc(idx)
la.Vector#unshift(...args)

qm

qm
qm.config([configPath][, overwrite][, portN][, cacheSize])
qm.create([configPath][, schemaPath][, clear])
qm.flags
qm.open([configPath][, readOnly])
qm.RecSet#saveCsv(opts)
qm.stats()
qm.verbosity([level])
qm.version
qm~BaseConstructorParam
qm~BaseLoadCSVParam
qm~DetailKeyObject
qm~FeatureExtractor
qm~FeatureExtractorCategorical
qm~FeatureExtractorConstant
qm~FeatureExtractorDateWindow
qm~FeatureExtractorJoin
qm~FeatureExtractorJsfunc
qm~FeatureExtractorMultinomial
qm~FeatureExtractorNumeric
qm~FeatureExtractorPair
qm~FeatureExtractorRandom

qm~FeatureExtractorSparseVector
qm~FeatureExtractorText
qm~FeatureTokenizer
qm~PerformanceStat
qm~PerformanceStatBase
qm~PerformanceStatStore
qm~QMinerFlags
qm~QueryObject
qm~SchemaDef
qm~SchemaFieldDef
qm~SchemaJoinDef
qm~SchemaKeyDef
qm~SchemaTimeWindowDef
qm~StreamAggrAggrResampler
qm~StreamAggrAnomalyDetectorNN
qm~StreamAggregator
qm~StreamAggrEMA
qm~StreamAggrEMASpVec
qm~StreamAggrFeatureSpace
qm~StreamAggrHistogram
qm~StreamAggrMax
qm~StreamAggrMerger

qm~StreamAggrMin
qm~StreamAggrMovingAverage
qm~StreamAggrMovingCorrelation
qm~StreamAggrMovingCovariance
qm~StreamAggrMovingVariance
qm~StreamAggrPageHinkley
qm~StreamAggrRecordBuffer
qm~StreamAggrRecordSwitch
qm~StreamAggrResampler
qm~StreamAggrSimpleLinearRegression
qm~StreamAggrSimpleLinearRegressionResult
qm~StreamAggrSlottedHistogram
qm~StreamAggrSparseVecSum
qm~StreamAggrSum
qm~StreamAggrTDigest
qm~StreamAggrThreshold
qm~StreamAggrTimeSeriesTick
qm~StreamAggrTimeSeriesWindow
qm~StreamAggrTimeSeriesWindowVector
qm~StreamAggrVecDiff
qm~StreamAggrWindowQuantiles

qm.Base

qm.Base(paramObj)
qm.Base#close()
qm.Base#createStore(storeDef[, storeSizeInMB])
qm.Base#garbageCollect([max_time])
qm.Base#getStats()

qm.Base#getStoreList()
qm.Base#getStreamAggr(saName)
qm.Base#getStreamAggrNames()
qm.Base#getStreamAggrStats()
qm.Base#isClosed()

qm.Base#isStore(name)
qm.Base#loadCSV(opts[, callback])
qm.Base#partialFlush([window])
qm.Base#search(query)
qm.Base#store(name)

qm.CircularRecordBuffer

qm.CircularRecordBuffer([params])
qm.CircularRecordBuffer#load(fin)

qm.CircularRecordBuffer#push(rec)
qm.CircularRecordBuffer#save(fout)

qm.FeatureSpace

qm.FeatureSpace(base, arg)
qm.FeatureSpace.prototyp.extractFeature(idx, val)
qm.FeatureSpace#addFeatureExtractor(ftExt)
qm.FeatureSpace#clear()
qm.FeatureSpace#dim
qm.FeatureSpace#dims

qm.FeatureSpace#extractMatrix(rs[, idx])
qm.FeatureSpace#extractSparseMatrix(rs[, idx])
qm.FeatureSpace#extractSparseVector(rec[, idx])
qm.FeatureSpace#extractVector(rec[, idx])
qm.FeatureSpace#filter(vec, idx[, keepOffset])
qm.FeatureSpace#getFeature(idx)

qm.FeatureSpace#getFeatureExtractor(idx)
qm.FeatureSpace#invertFeature(idx, val)
qm.FeatureSpace#invertFeatureVector(ftr)
qm.FeatureSpace#save(fout)
qm.FeatureSpace#updateRecord(rec)
qm.FeatureSpace#updateRecords(rs)

qm.Iterator

qm.Iterator()
qm.Iterator#next()

qm.Iterator#record
qm.Iterator#store

qm.Record

qm.Record()
qm.Record#$addJoin(joinName, joinRecord[, joinFrequency])
qm.Record#$clone()

qm.Record#$delJoin(joinName, joinRecord[, joinFrequency])
qm.Record#$fq
qm.Record#$id

qm.Record#$name
qm.Record#store
qm.Record#toJSON([joinRecords][, joinRecordFields][, sysFields])

qm.RecordSet

qm.RecordSet()
qm.RecordSet#clone()
qm.RecordSet#deleteRecords(rs)
qm.RecordSet#each(callback)
qm.RecordSet#empty
qm.RecordSet#filter(callback)
qm.RecordSet#filterByField(fieldName, minVal, maxVal)
qm.RecordSet#filterByFq([minFq][, maxFq])
qm.RecordSet#filterById([minId][, maxId])
qm.RecordSet#getMatrix(fieldName)

qm.RecordSet#getVector(fieldName)
qm.RecordSet#join(joinName[, sampleSize])
qm.RecordSet#length
qm.RecordSet#map(callback)
qm.RecordSet#reverse()
qm.RecordSet#sample(num)
qm.RecordSet#setDiff(rs)
qm.RecordSet#setIntersect(rs)
qm.RecordSet#setUnion(rs)
qm.RecordSet#shuffle([seed])

qm.RecordSet#sort(callback)
qm.RecordSet#sortByField(fieldName[, asc])
qm.RecordSet#sortByFq([asc])
qm.RecordSet#sortById([asc])
qm.RecordSet#split(callback)
qm.RecordSet#store
qm.RecordSet#toJSON()
qm.RecordSet#trunc(limit_num[, offset_num])
qm.RecordSet#weighted

qm.RecordVector

qm.RecordVector(base[, fin])
qm.RecordVector#length

qm.RecordVector#push(rec)
qm.RecordVector#save(fout)

qm.Store

qm.Store()
qm.Store#addStreamAggr(arg)
qm.Store#addTrigger(trigger)
qm.Store#allRecords
qm.Store#backwardIter
qm.Store#base
qm.Store#cell(recId, fieldName)
qm.Store#clear([num])
qm.Store#each(callback)
qm.Store#empty
qm.Store#field(fieldName)
qm.Store#fields
qm.Store#first

qm.Store#forwardIter
qm.Store#getMatrix(fieldName)
qm.Store#getStreamAggrNames()
qm.Store#getVector(fieldName)
qm.Store#inspect(depth)
qm.Store#isDate(fieldName)
qm.Store#isNumeric(fieldName)
qm.Store#isString(fieldName)
qm.Store#joins
qm.Store#key(keyName)
qm.Store#keys
qm.Store#last
qm.Store#length

qm.Store#loadJson(file[, limit])
qm.Store#map(callback)
qm.Store#name
qm.Store#newRecord(obj)
qm.Store#newRecordSet(idVec)
qm.Store#push(rec[, triggerEvents])
qm.Store#recordByName(recName)
qm.Store#resetStreamAggregates()
qm.Store#sample(sampleSize)
qm.Store#toJSON()
qm.Store#triggerOnAddCallbacks([arg])

qm.StreamAggr

qm.StreamAggr(base, arg[, storeName])
qm.StreamAggr#getFeatureSpace()
qm.StreamAggr#getFloat([str])
qm.StreamAggr#getFloatAt(idx)
qm.StreamAggr#getFloatLength()
qm.StreamAggr#getFloatVector()
qm.StreamAggr#getInFloatVector()
qm.StreamAggr#getInteger([str])
qm.StreamAggr#getInTimestampVector()
qm.StreamAggr#getInValueVector()
qm.StreamAggr#getNumberOfRecords()
qm.StreamAggr#getOutFloatVector()

qm.StreamAggr#getOutTimestampVector()
qm.StreamAggr#getOutValueVector()
qm.StreamAggr#getParams()
qm.StreamAggr#getTimestamp()
qm.StreamAggr#getTimestampAt(idx)
qm.StreamAggr#getTimestampLength()
qm.StreamAggr#getTimestampVector()
qm.StreamAggr#getValueVector()
qm.StreamAggr#init
qm.StreamAggr#load(fin)
qm.StreamAggr#loadStateJson(state)
qm.StreamAggr#name

qm.StreamAggr#onAdd(rec[, Caller])
qm.StreamAggr#onDelete(rec[, Caller])
qm.StreamAggr#onStep([Caller])
qm.StreamAggr#onTime(ts[, Caller])
qm.StreamAggr#onUpdate(rec[, Caller])
qm.StreamAggr#reset()
qm.StreamAggr#save(fout)
qm.StreamAggr#saveJson([limit])
qm.StreamAggr#saveStateJson()
qm.StreamAggr#setParams(params)
qm.StreamAggr#val

statistics

statistics
statistics.getZScore(x, mu, sigma)

statistics.mean(input)
statistics.std(X[, flag][, dim])

statistics.zscore(mat[, flag][, dim])