Example: Prediction Intervals for Gradient Boosting Regression

Prediction Intervals for Gradient Boosting Regression

This example shows how quantile regression can be used to create prediction intervals.

import numpy as np
import matplotlib.pyplot as plt

from sklearn.ensemble import GradientBoostingRegressor

np.random.seed(1)


def f(x):
    """The function to predict."""
    return x * np.sin(x)

#----------------------------------------------------------------------
#  First the noiseless case
X = np.atleast_2d(np.random.uniform(0, 10.0, size=100)).T
X = X.astype(np.float32)

# Observations
y = f(X).ravel()

dy = 1.5 + 1.0 * np.random.random(y.shape)
noise = np	          			          		
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