Method fit

code/chapter7.py:198–205

(self, X, Y)

        self.n_models = n_models

    def fit(self, X, Y):
        self.models = []
        for i in range(self.n_models):
            print("training {} base model:".format(i))
            X_samp, Y_samp = bootstrap_sample(X, Y)
            model = DFN(hidden_dims_1=200, hidden_dims_2=10)
            model.fit(X_samp, Y_samp)
            self.models.append(model)

    def predict(self, X):
        model_preds = np.array([[np.argmax(t.forward(x)[0]) for x in X] for t in self.models])