def benchmark_sgd_momentum(self): bmsvmsgdmomentum = BenchmarkSGDMomentum.BenchmarkSGDMomentum( exp_name=self.exp_name, training_file=self.training_file, testing_file=self.testing_file, alpha=self.alpha, C=self.C, gamma=self.gamma, features=self.n_features, epochs=self.epochs, labelfix=self.labelfix, randomize=self.randomize, split=self.split) bmsvmsgdmomentum.load_data() bmsvmsgdmomentum.train() bmsvmsgdmomentum.test() bmsvmsgdmomentum.stats()
kernel = 'rbf' minibatch_size = 1000 minibatch = True C=1 exp_name = dataset repetitions = range(0,10) tolerance = 0.01 bmsvmsgd = BenchmarkSgdSvm.BenchmarkSgdSVM(exp_name=exp_name, training_file=training_file, testing_file=testing_file, alpha=alpha, features=features, epochs=epochs, labelfix=labelfix, randomize=randomize, split=split, auto=True) bmsvmsgdmomentum = BenchmarkSGDMomentum.BenchmarkSGDMomentum(exp_name=exp_name, training_file=training_file, testing_file=testing_file, alpha=alpha, C=C, gamma=gamma, features=features, epochs=epochs, labelfix=labelfix, randomize=randomize, split=split) bmsvmsgdada = BenchmarkSGDAda.BenchmarkSGDAda(exp_name=exp_name, training_file=training_file, testing_file=testing_file, alpha=alpha, features=features, epochs=epochs, labelfix=labelfix, randomize=randomize, split=split, auto=True, bulk=bulk) bmsvmsgdrmsprop = BenchmarkSGDRMSProp.BenchmarkSGDRMSProp(exp_name=exp_name, training_file=training_file, testing_file=testing_file, alpha=alpha, features=features, epochs=epochs, labelfix=labelfix, randomize=randomize, split=split, auto=True, bulk=bulk) bmsvmsgdadam = BenchmarkSGDAdam.BenchmarkSGDAdam(exp_name=exp_name, training_file=training_file,