DummyRegressor

• Crea un estimador que pronostica con reglas simples.

• Se usa como linea base de comparación con otros modelos.

import numpy as np
from sklearn.dummy import DummyRegressor

X = np.array([1.0, 2.0, 3.0, 4.0])
y = np.array([2.0, 3.0, 5.0, 10.0])

dummy_regr = DummyRegressor(
    # -------------------------------------------------------------------------
    # Strategy to use to generate predictions.
    # * "mean": always predicts the mean of the training set.
    # * "median": always predicts the median of the training set.
    # * "quantile": always predicts a specified quantile of the training set,
    #   provided with the quantile parameter.
    # * "constant": always predicts a constant value that is provided by the
    #   user.
    strategy="mean",
    # -------------------------------------------------------------------------
    # The explicit constant as predicted by the “constant” strategy. This
    # parameter is useful only for the “constant” strategy.
    constant=None,
    # -------------------------------------------------------------------------
    # The quantile to predict using the “quantile” strategy. A quantile of 0.5
    # corresponds to the median, while 0.0 to the minimum and 1.0 to the
    # maximum.
    quantile=None,
)


dummy_regr.fit(X, y)

DummyRegressor()

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dummy_regr.predict(X)

array([5., 5., 5., 5.])

dummy_regr.score(X, y)

0.0