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  "Title": "CHAID and Exhaustive CHAID Decision Trees",
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  "Authors@R": "person(\"Osamu\", \"Morimoto\", email = \"galactic.supermarket@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\"))",
  "Description": "An implementation of the CHAID (Chi-squared Automatic\nInteraction Detection) decision tree algorithm of Kass (1980)\n<doi:10.2307/2986296> and the Exhaustive CHAID variant of\nBiggs, de Ville, and Suen (1991)\n<doi:10.1080/02664769100000005>, as specified in the 'IBM SPSS'\nStatistics Algorithms documentation. Supports nominal, ordinal\n(with floating missing category), and continuous predictors,\nand nominal, ordinal, and continuous response variables using\nPearson chi-squared, Goodman row-effects, and one-way ANOVA F\ntests respectively. Includes prediction, rule extraction, gains\nand lift analysis, validation on holdout data, and\nvisualization via base graphics, 'Graphviz' DOT, 'plotly', and\nconversion to 'partykit' objects.",
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  "Encoding": "UTF-8",
  "Language": "en-GB",
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  "BugReports": "https://github.com/morimotoosamu/chaidr/issues",
  "Repository": "https://morimotoosamu.r-universe.dev",
  "Date/Publication": "2026-08-09 02:19:57 UTC",
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      "title": "Fit a CHAID or Exhaustive CHAID decision tree",
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        "chaid"
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      "title": "Summary table of CHAID terminal nodes",
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      ]
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        "実例2: penguins — Exhaustive が簡潔な構造を選ぶ",
        "なぜ結果が変わるのか — Bonferroni 乗数 B の構造差",
        "計算コストの実測",
        "Exhaustive の副作用: 高カーディナリティ変数への偏り",
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        "4.3 重み",
        "4.4 欠損値（Floating カテゴリ）",
        "4.5 予測変数間の多重比較補正（adjust_across）",
        "4.6 一般的な二分木（CART / rpart）との比較",
        "4.7 レポーティング機能（テーブル・ルール・重要度・ゲイン・検証）",
        "4.8 誤分類コスト行列（costs）",
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