def train_svm_repeatedly(kernel,
train_X,
train_y,
valid_X,
valid_y,
test_X,
test_y,
masks_list=None):
metrics_bundles = []
for mask in masks_list:
metrics_bundles.append(
train_svm(kernel,
train_X,
train_y,
valid_X,
valid_y,
test_X,
test_y,
mask=mask))
train_metrics, valid_metrics, test_metrics = zip(*metrics_bundles)
valid_test_accs = zip(list(valid_metrics), list(test_metrics))
valid_test_acc_curves(valid_test_accs)
get_avg_metrics(train_metrics)
get_avg_metrics(valid_metrics)
get_avg_metrics(test_metrics)
def train_weighted_voting_repeatedly(train_X,
train_y,
valid_X,
valid_y,
test_X,
test_y,
threshold=0.5,
masks_list=None):
metrics_bundles = []
for mask in masks_list:
metrics_bundles.append(
train_weighted_voting('f1score',
train_X,
train_y,
valid_X,
valid_y,
test_X,
test_y,
mask=mask))
train_metrics, valid_metrics, test_metrics = zip(*metrics_bundles)
valid_test_accs = zip(list(valid_metrics), list(test_metrics))
valid_test_acc_curves(valid_test_accs)
get_avg_metrics(train_metrics)
get_avg_metrics(valid_metrics)
get_avg_metrics(test_metrics)
def train_neural_net_repeatedly(train_X,
train_y,
valid_X,
valid_y,
test_X,
test_y,
iterations=100):
metrics_bundles = []
for i in range(iterations):
metrics_bundles.append(
train_neural_net(train_X, train_y, valid_X, valid_y, test_X,
test_y))
train_metrics, valid_metrics, test_metrics = zip(*metrics_bundles)
valid_test_accs = zip(list(valid_metrics), list(test_metrics))
valid_test_acc_curves(valid_test_accs, "Artificial Neural Network")
get_avg_metrics(train_metrics)
get_avg_metrics(valid_metrics)
get_avg_metrics(test_metrics)