Mãos à Obra: Aprendizado de Máquina com Scikit-Learn e TensorFlow

Curvas de Aprendizado | 129

from sklearn.metrics import mean_squared_error

from sklearn.model_selection import train_test_split

def plot_learning_curves(model, X, y):

X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2)

train_errors, val_errors = [], []

for m in range(1, len(X_train)):

model.fit(X_train[:m], y_train[:m])

y_train_predict = model.predict(X_train[:m])

y_val_predict = model.predict(X_val)

train_errors.append(mean_squared_error(y_train_predict, y_train[:m]))

val_errors.append(mean_squared_error(y_val_predict, y_val))

plt.plot(np.sqrt(train_errors), "r-+", linewidth=2, label="train")

plt.plot(np.sqrt(val_errors), ...