Sklearn实现稳健回归

最新推荐文章于 2025-02-16 08:33:22 发布

数据科学家修炼之道

最新推荐文章于 2025-02-16 08:33:22 发布

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分类专栏： AI # Sklearn笔记文章标签：机器学习 sklearn

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本文链接：https://blog.youkuaiyun.com/xiligey1/article/details/112467864

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from matplotlib import pyplot as plt
import numpy as np

from sklearn.linear_model import (
    LinearRegression, TheilSenRegressor, RANSACRegressor, HuberRegressor)
from sklearn.metrics import mean_squared_error
from sklearn.preprocessing import PolynomialFeatures
from sklearn.pipeline import make_pipeline

np.random.seed(42)

X = np.random.normal(size=400)
y = np.sin(X)
# Make sure that it X is 2D
X = X[:, np.newaxis]

X_test = np.random.normal(size=200)
y_test = np.sin(X_test)
X_test = X_test[:, np.newaxis]

y_errors = y.copy()