def main():
# Load the dataset
df = pd.read_csv('linear_regression_test_data.csv')
# Load x and y only
input_data = df[['x', 'y']]
pca_object = My_PCA()
eigen_values, eigen_vectors, projections = pca_object.performPCA(
input_data, False)
print 'Eigen Values are: '
print eigen_values
print 'Eigen Vectors are: '
print eigen_vectors
print 'Projections are: '
print projections
#question_1_plots(df,eigen_vectors)
linear_regression = LinearRegression()
estimated_y = linear_regression.linear_regression(input_data)
#plot_regression_line(estimated_y,input_data)
# Now plot all together
#plot_all_together(df,eigen_vectors,estimated_y)
# --------- Question 2------------
# Linear Regression using scikit-learn
y_predicted, testing_dataset, training_dataset = linear_regression.linear_regression_sklearn(
) #Diabetes dataset
plot_diabetes_regression(y_predicted, testing_dataset)
