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,