queso_cluster.runners.base#

Functions#

findOptimalK(dataSquare, funcLst, criteriaLst[, converge])

kFinder(data)

runIntrinsic(edges, data)

runLabelSort(dataSquare, labelLine)

runOptimalKSearch(dataSquare, funcLst, checkLst)

runOptimization(k, sub_data, converge[, initialize])

runPrep(dataSquare, norm[, quSquare])

runStart(k, data, initialize[, seed])

Module Contents#

findOptimalK(dataSquare, funcLst, criteriaLst, converge=1e-06)[source]#
kFinder(data)[source]#
runIntrinsic(edges, data)[source]#
runLabelSort(dataSquare, labelLine)[source]#
runOptimalKSearch(dataSquare, funcLst, checkLst)[source]#
runOptimization(k, sub_data, converge, initialize='++')[source]#
runPrep(dataSquare, norm, quSquare=None, **kwargs)[source]#
runStart(k, data, initialize, seed=np.random.random())[source]#