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回帰のためのk-最近傍法アルゴリズム

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from sklearn.neighbors import KNeighborsRegressor

X, y = mglearn.datasets.make_wave(n_samples=40)

# 分割
X_train, X_test, y_train, y_test = train_test_split(
        X, y, random_state=0)

# インスタンス生成、最近傍点は3にセット
reg = KNeighborsRegressor(n_neighbors=3) 

# モデル学習
reg.fit(X_train, y_train)

# モデル評価
reg.score(X_test, y_test)

なお、回帰予測器はR2スコアを返す
※回帰モデルの予測精度をあらわす指標。0-1までの数値が返され、1に近づくほど高精度な予測

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