def model_complexity_exp_alpha1(self):
#TODO should we create a new learner object??
self.learner = ANNLearner(hidden_layer_sizes=(300, ))
self.expHelper = ExperimentHelper(self.splitter, self.learner, '1')
#param_range = np.array([(100),(200,),(300,),(400,),(500,)])
#param_range = np.array([0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1])
param_range = np.array([0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1])
self.expHelper.model_complexity_exp('alpha', param_range)
self.learner = ANNLearner(hidden_layer_sizes=(390, ))
self.expHelper = ExperimentHelper(self.splitter, self.learner, '2')
#param_range = np.array([(100),(200,),(300,),(400,),(500,)])
param_range = np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7])
#param_range = np.array([0.0001, 0.0005, 0.001, 0.005, 0.008])
self.expHelper.model_complexity_exp('alpha', param_range)
def model_complexity_exp11(self):
#TODO should we create a new learner object??
self.learner = ANNLearner()
self.expHelper = ExperimentHelper(self.splitter, self.learner)
param_range = np.array([(50, ), (
50,
50,
), (
50,
50,
50,
), (
50,
50,
50,
50,
), (
50,
50,
50,
50,
50,
)])
#param_range = np.array([100, 200,300,400, 500])
self.expHelper.model_complexity_exp('hidden_layer_sizes', param_range)
def model_complexity_exp_alpha2(self):
#TODO should we create a new learner object??
self.learner = ANNLearner()
self.expHelper = ExperimentHelper(self.splitter, self.learner, '2')
#param_range = np.array([(100),(200,),(300,),(400,),(500,)])
param_range = np.array([0.0001, 0.001, 0.01, 0.1, 1, 5])
self.expHelper.model_complexity_exp('alpha', param_range)
def experiment_run_test_bank2(self):
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(390, ),
learning_rate='constant',
solver='adam',
early_stopping=False)
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
def learning_curve_iter21_bank(self):
self.learner = ANNLearner(activation='relu',
alpha=0.01,
hidden_layer_sizes=(300, ),
learning_rate='constant',
solver='adam',
early_stopping=False)
self.expHelper = ExperimentHelper(self.splitter, self.learner,
'-iter-2')
self.expHelper.learning_curve_exp()
def model_complexity_exp_epoch2(self):
#TODO should we create a new learner object??
self.learner = ANNLearner(hidden_layer_sizes=(300, ),
alpha=0.0001,
early_stopping=False)
self.expHelper = ExperimentHelper(self.splitter, self.learner, '3')
#param_range = np.array([(100),(200,),(300,),(400,),(500,)])
#param_range = np.array([0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1])
param_range = np.array([1, 10, 50, 100, 200, 500, 1000])
self.expHelper.model_complexity_exp('max_iter', param_range)
def experiment_run_test_bank_iter2(self):
self.learner = ANNLearner(activation='relu',
alpha=0.06,
hidden_layer_sizes=(200, 200, 200, 200, 200,
200, 200),
learning_rate='constant',
solver='adam',
early_stopping=True,
max_iter=600,
momentum=0.4)
print('100, 100, 100, 100, 100, 100,50 alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
""" self.learner = ANNLearner(
def model_complexity_exp_epoch(self):
#TODO should we create a new learner object??
self.learner = ANNLearner(activation='relu',
alpha=0.01,
hidden_layer_sizes=(
50,
50,
50,
),
learning_rate='constant',
solver='adam',
early_stopping=True)
self.expHelper = ExperimentHelper(self.splitter, self.learner, '2')
#param_range = np.array([(100),(200,),(300,),(400,),(500,)])
#param_range = np.array([0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1])
param_range = np.array([1, 10, 50, 100, 200, 500])
self.expHelper.model_complexity_exp('max_iter', param_range)
def __init__(self, reader, helper, splitter):
self.reader = reader
self.helper = helper
self.learner = ANNLearner()
self.splitter = splitter
self.expHelper = ExperimentHelper(self.splitter, self.learner)
def experiment_run_test_bank_iter(self):
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(390, 100),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('390,100')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(200, 200, 200),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('200, 200, 200')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(400, 400, 400),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('400, 400, 400')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(500, 500, 500),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('500, 500, 500')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(200, 300, 400),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('200, 300, 400')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.7,
hidden_layer_sizes=(390, 100),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('390,100')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(200, 200, 200),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('200, 200, 200 alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(400, 400, 400),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('400, 400, 400 alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(500, 500, 500),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('500, 500, 500 alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(200, 300, 400),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('200, 300, 400 alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(
100,
100,
100,
100,
),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('100, 100, 100, 100, alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(100, 100, 100, 100, 100),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('100, 100, 100, 100, 100, alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(100, 100, 100, 100, 100,
50),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('100, 100, 100, 100, 100, 50, alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()
self.learner = ANNLearner(activation='relu',
alpha=0.3,
hidden_layer_sizes=(50, 50, 50, 50, 50, 50),
learning_rate='constant',
solver='adam',
early_stopping=False)
print('50, 50, 50, 50, 50, 50, alpha 0.3')
self.expHelper = ExperimentHelper(self.splitter, self.learner)
self.expHelper.experiment_run_test()