random.seed(21)
examplesFileName = SvmInfoExperiment.getExamplesFileName()
sampleSize = 86755
svmEgoSimulator = SvmEgoSimulator(examplesFileName)
preprocessor = svmEgoSimulator.getPreProcessor()
centerValues = preprocessor.getCentreVector()
svmParamsFileName = SvmInfoExperiment.getSvmParamsFileName() + "Linear.mat"
logging.info("Using SVM params from file " + svmParamsFileName)
C, kernel, kernelParamVal, errorCost = SvmInfoExperiment.loadSvmParams(svmParamsFileName)
svmEgoSimulator.trainClassifier(C, kernel, kernelParamVal, errorCost, sampleSize)
weights, b = svmEgoSimulator.getWeights()
numpy.set_printoptions(precision=3)
#Print the weights then their sorted values by indices and then value
sortedWeightsInds = numpy.flipud(numpy.argsort(abs(weights)))
sortedWeights = numpy.flipud(weights[numpy.argsort(abs(weights))])
egoCsvReader = EgoCsvReader()
questionIds = egoCsvReader.getEgoQuestionIds()
questionIds.extend(egoCsvReader.getAlterQuestionIds())
print(weights)
numRankedItems = 20
for i in range(0,numRankedItems):
