naive_bayes_fit.py

def fit(self):
    for c in self.classes:
        x_c = self.X[c == self.y]  # Get a feature vector that belongs to the class
        self.means.append(x_c.mean(axis=0))  # axis = 0 => column-wise Mean
        self.stds.append(x_c.std(axis=0))  # axis = 0 => column-wise STD
        self.priors.append(len(x_c) / len(self.X))  # Calculate frequency of each class