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]
learner.setEpsilon(epsilon)
learner.normModelSelect = True
paramDict = {}
paramDict["setC"] = Cs
numParams = Cs.shape[0]
#datasets = [datasets[1]]
for datasetName, numRealisations in datasets:
logging.debug("Dataset " + datasetName)
errors = numpy.zeros(numRealisations)
