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    "title": "scikit-learnのPipelineで前処理と分類をまとめて検証する",
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      "送信範囲・接続先・認証・費用と資源を確認する",
      "公式の利用開始案内でscikit-learnの対応環境・導入方法・利用条件を確認し、検証用の環境へ用意します。"
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    "unsuitable_for": "データ漏洩を確認せず高い評価値だけを採用する用途。",
    "purpose": "scikit-learnのPipelineで前処理と分類をまとめて検証する",
    "composition": "scikit-learn + Python",
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      "小さな検証データを学習・評価へ分ける",
      "前処理と分類器をPipelineで接続してfitする",
      "未使用の評価入力で結果を確認する"
    ],
    "verification": "前処理も学習データでfitされ、評価データを先に混ぜていないことを確認します。",
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