from sklearn.metrics import accuracy_score
print(accuracy_score(y, yhat))

# precision, positive predicted value = TP / (TP + FP)
# recall, sensitivity, true positive rate = TP / (TP + FN)
# f1-score ((.854 * 2)/1.84) https://en.wikipedia.org/wiki/F1_score

from sklearn.metrics import classification_report
print(classification_report(y, yhat))

from sklearn.metrics import confusion_matrix
print(confusion_matrix(y, yhat))