pp = pprint.PrettyPrinter()
model = LinearModel(train='data/PA1_train.pkl',
validation='data/PA1_dev.pkl',
test='data/PA1_test.pkl',
target='price',
rate=1e-05,
lam=0.001,
eps=0.5,
normalize=True)
names = model.weight_labels
learned_model = model.train_model(50000)
val_predictions = model.predict_validation(
learned_model['weights'])['predictions']
test_predictions = model.predict_test(
(learned_model['weights']))['predictions']
prediction_output = pathlib.Path('model_output/predictions.pkl')
prediction_file = pathlib.Path('model_output/predictions.txt')
pred_output_path = pathlib.Path(__file__).parent.resolve().joinpath(
prediction_output)
pred_file_path = pathlib.Path(__file__).parent.resolve().joinpath(
prediction_file)
# Save predictions
with open(pred_output_path, 'wb') as fp:
pickle.dump(test_predictions, fp, pickle.HIGHEST_PROTOCOL)
# Output predictions to text file
with open(pred_file_path, 'w') as f:
