for line in f.readlines():
X_1 = float(line.replace('\n', '').split(',')[0])
X_2 = float(line.replace('\n', '').split(',')[1])
y.append(X_2)
x = (X_1, X_2)
X.append(x)
return np.asarray(X), np.asarray(y)
# calling read_data function and returns X, y
X, y = read_data('data.txt')
# declares model as follows.
model = LinearRegression(X, y, theta=[0, 0], num_iter=1000, learning_rate=0.001, verbose=True)
# plotting data
model.plot_data()
# starting to train data
model.train(X, y)
# plots cost history.
model.plot_cost()
# plots decision boundary.
model.plot_line()
# compares model to sklearn.linear model.
print()
model.compare_to_Sklearn()
