# Task 2:
 
def sigmoid(x):
    return 1 / (1 + np.e**(-x))
def predict_class(x_data):
    prediction =  np.dot(x_data, model.coef_.T) + model.intercept_
    prediction = sigmoid(prediction)
 
    return (prediction >= 0.5).reshape(-1).astype(int)
 
 
# Task 3:
def calc_accuracy(y_true, y_pred):
    total = len(y_true)
    cnt = 0
    for i in range(total):
        if y_true[i] == y_pred[i]:
            cnt += 1
    return cnt / total
 
 
# Task 4: Test these 2 functions

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