# Is it possible to know the output vectors of MLP Classifier of scikit learn?

I'm a beginner with scikiti-learn library. I have an ANN with 3 input, 2 hidden layers and 3 output.

mlp = MLPClassifier(hidden_layer_sizes= hidden_layers,max_iter=iterations, activation=activation_fun)


I read on the documentation that the classifier uses softmax for the output activation function and cross-entropy loss function. I have a multi-class problem where the three outputs will predict the classes 0,1,2. My question is that. How can I retrieve the vectors that enconds the classes 0,1,2? example: [1,0,0] -> 0 [0,1,0] -> 1 [0,0,1] -> 2

If you are interested on the probability output of your model, simply call mlp.predict_proba(X)