Exemplos de MaxLocalAUC.lmbdas em Python

Exemplo n.º 1

Arquivo: RegularisationExp5.py Projeto: charanpald/wallhack

u = 0.1
w = 1-u
k2 = 64
eps = 10**-6
maxLocalAuc = MaxLocalAUC(k2, w, eps=eps, stochastic=True)
maxLocalAuc.alpha = 0.1
maxLocalAuc.alphas = 2.0**-numpy.arange(0, 5, 1)
maxLocalAuc.folds = 1
maxLocalAuc.initialAlg = "rand"
maxLocalAuc.itemExpP = 0.0
maxLocalAuc.itemExpQ = 0.0
maxLocalAuc.ks = numpy.array([k2])
maxLocalAuc.lmbdaU = 0.0
maxLocalAuc.lmbdaV = 0.0
maxLocalAuc.lmbdas = 2.0**-numpy.arange(0, 8)
maxLocalAuc.loss = "hinge"
maxLocalAuc.maxIterations = 500
maxLocalAuc.maxNorms = 2.0**numpy.arange(-2, 5, 0.5)
maxLocalAuc.metric = "f1"
maxLocalAuc.normalise = True
maxLocalAuc.numAucSamples = 10
maxLocalAuc.numProcesses = multiprocessing.cpu_count()
maxLocalAuc.numRecordAucSamples = 100
maxLocalAuc.numRowSamples = 30
maxLocalAuc.rate = "constant"
maxLocalAuc.recordStep = 10
maxLocalAuc.rho = 1.0
maxLocalAuc.t0 = 1.0
maxLocalAuc.t0s = 2.0**-numpy.arange(7, 12, 1)
maxLocalAuc.validationSize = 3

Exemplo n.º 2

Arquivo: LossROCExp.py Projeto: charanpald/wallhack

numRecordAucSamples = 200

k2 = 8
u2 = 0.5
w2 = 1-u2
eps = 10**-4
lmbda = 0.0
maxLocalAuc = MaxLocalAUC(k2, w2, eps=eps, lmbdaU=lmbda, lmbdaV=lmbda, stochastic=True)
maxLocalAuc.alpha = 0.05
maxLocalAuc.alphas = 2.0**-numpy.arange(0, 5, 1)
maxLocalAuc.folds = 1
maxLocalAuc.initialAlg = "rand"
maxLocalAuc.itemExpP = 0.0
maxLocalAuc.itemExpQ = 0.0
maxLocalAuc.ks = numpy.array([k2])
maxLocalAuc.lmbdas = numpy.linspace(0.5, 2.0, 7)
maxLocalAuc.maxIterations = 500
maxLocalAuc.metric = "f1"
maxLocalAuc.normalise = True
maxLocalAuc.numAucSamples = 10
maxLocalAuc.numProcesses = 1
maxLocalAuc.numRecordAucSamples = 100
maxLocalAuc.numRowSamples = 30
maxLocalAuc.rate = "constant"
maxLocalAuc.recordStep = 10
maxLocalAuc.rho = 1.0
maxLocalAuc.t0 = 1.0
maxLocalAuc.t0s = 2.0**-numpy.arange(7, 12, 1)
maxLocalAuc.validationSize = 3
maxLocalAuc.validationUsers = 0

Exemplo n.º 3

Arquivo: RegularisationExp2.py Projeto: charanpald/wallhack

numRecordAucSamples = 200

k2 = 64
u2 = 0.5
w2 = 1-u2
eps = 10**-8
lmbda = 0.1
maxLocalAuc = MaxLocalAUC(k2, w2, eps=eps, lmbdaU=lmbda, lmbdaV=lmbda, stochastic=True)
maxLocalAuc.alpha = 0.05
maxLocalAuc.alphas = 2.0**-numpy.arange(0, 9, 1)
maxLocalAuc.folds = 1
maxLocalAuc.initialAlg = "rand"
maxLocalAuc.itemExpP = 0.0
maxLocalAuc.itemExpQ = 0.0
maxLocalAuc.ks = numpy.array([k2])
maxLocalAuc.lmbdas = 2.0**-numpy.arange(-2, 5, 3)
maxLocalAuc.loss = "hinge"
maxLocalAuc.maxIterations = 500
maxLocalAuc.maxNormU = 100
maxLocalAuc.maxNormV = 100
maxLocalAuc.metric = "f1"
maxLocalAuc.normalise = True
maxLocalAuc.numAucSamples = 10
maxLocalAuc.numProcesses = 1
maxLocalAuc.numRecordAucSamples = 100
maxLocalAuc.numRowSamples = 30
maxLocalAuc.rate = "constant"
maxLocalAuc.recordStep = 10
maxLocalAuc.rho = 1.0
maxLocalAuc.t0 = 1.0
maxLocalAuc.t0s = 2.0**-numpy.arange(7, 12, 1)