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# Imports
import csv
import importlib
from scripts import proj1_helpers, implementation, helpers, feature_processing
import numpy as np
Configuration
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train_path = '../data/train.csv'
test_path = '../data/test.csv'
output_path = '../data/baseline_submission.csv'
Loading data
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def get_tx_y_standardized(path):
y, X, ids = proj1_helpers.load_csv_data(path)
X_s, _, _ = feature_processing.standardize(X)
tx = feature_processing.add_polynomial(X_s, [])
return tx, y, ids
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# loading data
tx_train, y_train, ids_train = get_tx_y_standardized(train_path)
tx_test, y_test, ids_test = get_tx_y_standardized(test_path)
Training the model
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w, l = implementation.least_squares(y_train, tx_train)
Making predictions and saving to file
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y_pred = proj1_helpers.predict_labels(w, tx_test)
proj1_helpers.create_csv_submission(ids_test, y_pred, output_path)
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