from exp.modelselect.ModelSelectUtils import ModelSelectUtils from sandbox.util.Sampling import Sampling from apgl.predictors.LibSVM import LibSVM import matplotlib.pyplot as plt logging.basicConfig(stream=sys.stdout, level=logging.DEBUG) numpy.seterr(all="raise") numpy.random.seed(21) dataDir = PathDefaults.getDataDir() dataDir += "modelPenalisation/regression/" outputDir = PathDefaults.getOutputDir() + "modelPenalisation/regression/SVR/" figInd = 0 loadMethod = ModelSelectUtils.loadRegressDataset datasets = ModelSelectUtils.getRegressionDatasets(True) numProcesses = multiprocessing.cpu_count() learner = LibSVM(kernel="rbf", processes=numProcesses, type="Epsilon_SVR") learner.setChunkSize(3) Cs = 2.0**numpy.arange(-10, 14, 2, dtype=numpy.float) gammas = 2.0**numpy.arange(-10, 4, 2, dtype=numpy.float) epsilons = learner.getEpsilons() gammaInd = 3 gamma = gammas[gammaInd] learner.setGamma(gamma) epsilonInd = 0 epsilon = epsilons[epsilonInd]
showCART = True
showSVR = False
from itertools import cycle
lines = ["k-","k--","k-.","k:","k-x", "k-+"]
linecycler = cycle(lines)
if showSVR:
outputDir = PathDefaults.getOutputDir() + "modelPenalisation/regression/SVR/"
sampleSizes = numpy.array([50, 100, 200])
sampleMethods = ["CV"]
cvScalings = numpy.arange(0.6, 1.61, 0.2)
foldsSet = numpy.arange(2, 13, 2)
datasetNames = ModelSelectUtils.getRegressionDatasets()
fileNameSuffix = 'Results'
summary(datasetNames, sampleSizes, foldsSet, cvScalings, sampleMethods, fileNameSuffix)
plotDatasetNames = [datasetNames[7]]
plotAlphas(plotDatasetNames, sampleSizes, foldsSet, cvScalings, sampleMethods, fileNameSuffix)
sampleSizes = numpy.array([25, 50, 100])
sampleMethods = ["CV"]
cvScalings = numpy.arange(0.6, 1.61, 0.2)
foldsSet = numpy.arange(10, 51, 10)
datasetNames = ModelSelectUtils.getRegressionDatasets()
fileNameSuffix = "ResultsExt"
summary(datasetNames, sampleSizes, foldsSet, cvScalings, sampleMethods, fileNameSuffix, "GridResultsExt")
import matplotlib.pyplot as plt
from apgl.util import Evaluator
import sklearn.metrics
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
numpy.seterr(all="raise")
numpy.random.seed(45)
numpy.set_printoptions(linewidth=150)
dataDir = PathDefaults.getDataDir()
dataDir += "modelPenalisation/regression/"
outputDir = PathDefaults.getOutputDir() + "modelPenalisation/regression/SVR/"
figInd = 0
loadMethod = ModelSelectUtils.loadRegressDataset
datasets = ModelSelectUtils.getRegressionDatasets(True)
datasetName = datasets[9][0]
#sampleSizes = numpy.array([50, 100, 200])
sampleSizes = numpy.array([50, 100, 150, 200, 250, 300])
foldsSet = numpy.arange(2, 13, 1)
alpha = 1.0
Cs = 2.0**numpy.arange(-10, 14, 2, dtype=numpy.float)
gammas = 2.0**numpy.arange(-10, 4, 2, dtype=numpy.float)
epsilons = numpy.array([2**-2])
paramDict = {}
paramDict["setC"] = Cs
paramDict["setGamma"] = gammas
paramDict["setEpsilon"] = epsilons