Analyse the predictive power of your algorithm with Scikit-Learn. More at https://scikit-learn.org/

scikit_predictive_power.py

from sklearn.metrics import accuracy_score, recall_score, precision_score, f1_score

#True labels and predicted classifications
labels = [1, 0, 0, 1, 1, 1, 0, 1, 1, 1]
guesses = [0, 1, 1, 1, 1, 0, 1, 0, 1, 0]

#Calculate accuracy, recall, precision and f1 score
print(accuracy_score(labels, guesses))
print(recall_score(labels, guesses))
print(precision_score(labels, guesses))
print(f1_score(labels, guesses))