Curvas de aprendizaje

Introducción al Deep Learning con Keras

Miguel Esteban

Data Scientist & Founder

# Store initial model weights
init_weights = model.get_weights()

# Lists for storing accuracies
train_accs = []
tests_accs = []

for train_size in train_sizes:
    # Split a fraction according to train_size
    X_train_frac, _, y_train_frac, _ = 
    train_test_split(X_train, y_train, train_size=train_size)

    # Set model initial weights
    model.set_weights(initial_weights)

    # Fit model on the training set fraction
    model.fit(X_train_frac, y_train_frac, epochs=100,
                  verbose=0,
                  callbacks=[EarlyStopping(monitor='loss', patience=1)])

    # Get the accuracy for this training set fraction
    train_acc = model.evaluate(X_train_frac, y_train_frac, verbose=0)[1]
    train_accs.append(train_acc)

    # Get the accuracy on the whole test set
    test_acc = model.evaluate(X_test, y_test, verbose=0)[1]
    test_accs.append(test_acc)
    print("Done with size: ", train_size)

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Introducción al Deep Learning con Keras