示例#1
0
 def benchmark_manual_sgd(self):
     bmsvmsgd = BenchmarkSgdSvm.BenchmarkSgdSVM(
         exp_name=self.exp_name,
         training_file=self.training_file,
         testing_file=self.testing_file,
         alpha=self.alpha,
         features=self.n_features,
         epochs=self.epochs,
         labelfix=self.labelfix,
         randomize=self.randomize,
         split=self.split,
         auto=False)
     bmsvmsgd.load_data()
     bmsvmsgd.train()
     bmsvmsgd.test()
     bmsvmsgd.stats()
示例#2
0
    eta = 0.1
    labelfix = False
    split = split
    randomize = True
    gamma = 1
    degree = 1
    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)