4C) MeanAbsError.py
from sklearn.metrics import mean_absolute_error as mae
actual = [2,3,5,5,9]
calculated = [3,3,8,7,6]
error = mae(actual,calculated)
print('mean absolute error:'+str(error))


4D) MeansqaError.py
from sklearn.metrics import mean_squared_error
Y_true = [1,1,2,2,4]
Y_pred = [0.6,1.29,1.99,2.69,3.4]
MSE = mean_squared_error(Y_true,Y_pred)
print(MSE)


4G) F1_score.py
import numpy as np
from sklearn.metrics import f1_score
actual = np.repeat([1,0], repeats=[160,240])
pred=np.repeat([1,0,1,0], repeats=[120,40,70,170])
print(f1_score(actual,pred))