import pandas as pd df=pd.read_csv('https://raw.githubusercontent.com/gtchandra/skema-Bootcamp1-students/master/RegressionMetrics.csv')

df

import pandas as pd import numpy as np data=pd.read_csv('https://raw.githubusercontent.com/gtchandra/skema-Bootcamp1-students/master/RegressionMetrics.csv')

len(data)

y = data['Y'].values y1 = data['y1'].values y2 = data['y2'].values y3 = data['y3'].values def compute_mse(array_tested: np.array) -> float: minus = y - array_tested minus_2 = minus ** 2 sum_minus_2 = np.sum(minus_2) return sum_minus_2 / len(minus_2) for df in [y1, y2, y3]: print(compute_mse(df))

def compute_rmse(array_tested: np.array) -> float: return np.sqrt(compute_mse(array_tested)) for df in [y1, y2, y3]: print(compute_rmse(df))

def compute_r_2(array_tested: np.array) -> float: rss = np.sum((y - array_tested)**2) tss = np.sum((y - np.mean(y))**2) return 1 - rss/tss for df in [y1, y2, y3]: print(compute_r_2(df))

def func(une_variable_locale: str): print(une_variable_locale) func("test")

df = pd.DataFrame(columns=['short', 'mid', 'long', 'index']) df

df['short'] = [15, 1, 4] df['mid'] = [5, 12, 3] df['long'] = [3, 4, 34] df['index'] = ['short', 'mid', 'long'] df = df.set_index('index') df

matrix = pd.DataFrame(columns=["T", "F", "index"]) matrix["index"] = ["T", "F"] matrix = matrix.set_index("index") matrix

matrix["T"]["T"] = sum(df[i][i] for i in df.index) matrix["F"]["F"] = matrix