{"id":3145,"date":"2022-02-27T12:23:12","date_gmt":"2022-02-27T04:23:12","guid":{"rendered":"https:\/\/egonlin.com\/?p=3145"},"modified":"2022-02-27T12:23:12","modified_gmt":"2022-02-27T04:23:12","slug":"%e7%ac%ac%e4%ba%8c%e7%af%87%ef%bc%9ascikit-learn%e5%ba%93%e4%b9%8badaboost%e7%ae%97%e6%b3%95","status":"publish","type":"post","link":"https:\/\/egonlin.com\/?p=3145","title":{"rendered":"\u7b2c\u4e8c\u7bc7\uff1ascikit-learn\u5e93\u4e4bAdaBoost\u7b97\u6cd5"},"content":{"rendered":"

scikit-learn\u5e93\u4e4bAdaBoost\u7b97\u6cd5<\/h1>\n

  \u5f53\u6211\u4eec\u5bf9Adaboost\u8c03\u53c2\u65f6\uff0c\u4e3b\u8981\u8981\u5bf9\u4e24\u90e8\u5206\u5185\u5bb9\u8c03\u53c2\uff0c\u7b2c\u4e00\u90e8\u5206\u662f\u5bf9Adaboost\u7684\u6846\u67b6\u8fdb\u884c\u8c03\u53c2\uff0c\u7b2c\u4e8c\u90e8\u5206\u662f\u5bf9\u5f31\u5b66\u4e60\u5668\u8c03\u53c2\u3002\u672c\u6587\u4e3b\u8981\u4ecb\u7ecdAdaBoost\u7684\u4e24\u4e2a\u6a21\u578bAdaBoostClassifier<\/code>\u548cAdaBoostRegressor<\/code>\uff0c\u4f1a\u8be6\u89e3\u4ecb\u7ecdAdaBoostClassifier<\/code>\u6a21\u578b\uff0c\u7136\u540e\u4f1a\u5bf9\u6bd4\u7740\u8bb2\u89e3AdaBoostRegressor<\/code>\u6a21\u578b\u3002<\/p>\n

  \u63a5\u4e0b\u6765\u5c06\u4f1a\u8ba8\u8bba\u4e0a\u8ff0\u4e24\u8005\u7684\u533a\u522b\uff0c\u7531\u4e8e\u662f\u4ece\u5b98\u65b9\u6587\u6863\u7ffb\u8bd1\u800c\u6765\uff0c\u7ffb\u8bd1\u4f1a\u7565\u6709\u504f\u9887\uff0c\u6709\u5174\u8da3\u7684\u4e5f\u53ef\u4ee5\u53bbscikit-learn\u5b98\u65b9\u6587\u6863\u67e5\u770bhttps:\/\/scikit-learn.org\/stable\/modules\/classes.html#module-sklearn.ensemble<\/p>\n

AdaBoostClassifier<\/h1>\n

\u4f7f\u7528\u573a\u666f<\/h2>\n

  AdaBoostClassifier<\/code>\u6a21\u578b\u4e3b\u8981\u89e3\u51b3\u5206\u7c7b\u95ee\u9898\uff0c\u5e76\u4e14\u5b83\u5728scikit-learn\u5e93\u4e2d\u4f7f\u7528\u4e86\u4e24\u79cd\u5206\u7c7b\u7b97\u6cd5\u7684\u5b9e\u73b0\uff0c\u5206\u522b\u662fSAMME\u548cSAMME.R\u3002<\/p>\n

\u53c2\u6570<\/h2>\n
    \n
  • base_estimator\uff1a<\/strong>\u5f31\u5206\u7c7b\u5668\u7c7b\u578b\uff0cobject\u7c7b\u578b\u3002\u7406\u8bba\u4e0a\u53ef\u4ee5\u9009\u62e9\u4efb\u4f55\u4e00\u4e2a\u5f31\u5206\u7c7b\u5668\uff0c\u4e0d\u8fc7\u9700\u8981\u652f\u6301\u6837\u672c\u6743\u91cd\uff0c\u4e00\u822c\u7528\u51b3\u7b56\u6811\u6216\u795e\u7ecf\u7f51\u7edc\u3002\u5982\u679calgorithm=’SAMME.R’\uff0c\u5f31\u5206\u7c7b\u5668\u5e94\u8be5\u652f\u6301\u6982\u7387\u9884\u6d4b\uff0c\u5373\u652f\u6301predict_proba()\u65b9\u6cd5\u3002\u5982\u679c\u4e3a\u9ed8\u8ba4\u503c\uff0c\u7b97\u6cd5\u4f1a\u9009\u62e9\u4e00\u4e2a\u6700\u5927\u6df1\u5ea6\u4e3a1\u7684\u51b3\u7b56\u6811\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n
  • n_estimators\uff1a<\/strong>\u6700\u5927\u8fed\u4ee3\u6b21\u6570\uff0cint\u7c7b\u578b\u3002\u5f31\u5b66\u4e60\u5668\u7684\u6700\u5927\u8fed\u4ee3\u6b21\u6570\uff0c\u5982\u679c\u8fed\u4ee3\u6b21\u6570\u592a\u5c0f\uff0c\u5bb9\u6613\u6b20\u62df\u5408\uff1b\u5982\u679c\u8fed\u4ee3\u6b21\u6570\u592a\u5927\uff0c\u5bb9\u6613\u8fc7\u62df\u5408\u3002\u9ed8\u8ba4\u4e3a50\u3002<\/li>\n
  • learning_rate\uff1a<\/strong>\u6743\u91cd\u7f29\u51cf\u7cfb\u6570\uff0cfloat\u7c7b\u578b\u3002\u8fd9\u4e2a\u53c2\u6570\u662f\u6b63\u5219\u5316\u9879\u7684\u53c2\u6570$\\lambda$\u3002\u8f83\u5c0f\u7684$\\lambda$\u9700\u8981\u66f4\u591a\u7684\u8fed\u4ee3\u6b21\u6570\uff0c\u5373learning_rate\u548cn_estimators\u9700\u8981\u4e00\u8d77\u8c03\u53c2\u3002\u9ed8\u8ba4\u4e3a1\u3002<\/li>\n
  • algorithm\uff1a<\/strong>\u7b97\u6cd5\u7c7b\u578b\uff0cstr\u7c7b\u578b\u3002\u8be5\u53c2\u6570\u4e3b\u8981\u7528\u6765\u5ea6\u91cf\u5b66\u4e60\u5668\u7684\u6743\u91cd\u3002\u9ed8\u8ba4\u4e3a’SAMME.R’\u3002\n
      \n
    • ‘SAMME’\uff1a\u4f7f\u7528\u6837\u672c\u96c6\u5206\u7c7b\u6548\u679c\u4f5c\u4e3a\u5f31\u5206\u7c7b\u5668\u6743\u91cd<\/li>\n
    • ‘SAMME.R’\uff1a\u4f7f\u7528\u6837\u672c\u96c6\u5206\u7c7b\u7684\u9884\u6d4b\u6982\u7387\u5927\u5c0f\u4f5c\u4e3a\u5f31\u5206\u7c7b\u5668\u6743\u91cd<\/li>\n<\/ul>\n<\/li>\n
    • random_state\uff1a<\/strong>\u968f\u673a\u6570\u79cd\u5b50\uff0cint\u7c7b\u578b\u3002\u4f7f\u7528\u540e\u53ef\u4ee5\u4fdd\u8bc1\u968f\u673a\u6570\u4e0d\u4f1a\u968f\u7740\u65f6\u95f4\u7684\u53d8\u5316\u800c\u53d8\u5316\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<\/ul>\n

      \u5c5e\u6027<\/h2>\n
        \n
      • estimators_\uff1a<\/strong>list\u7c7b\u578b\u3002\u5f31\u5b66\u4e60\u96c6\u5408\u3002<\/li>\n
      • classes_\uff1a<\/strong>array\u7c7b\u578b\u3002\u7c7b\u522b\u5217\u8868\u3002<\/li>\n
      • nclasses<\/em>\uff1a<\/strong>int\u7c7b\u578b\u3002\u7c7b\u522b\u6570\u3002<\/li>\n
      • estimatorweights<\/em>\uff1a<\/strong>array\u7c7b\u578b\u3002\u6bcf\u4e2a\u5f31\u5b66\u4e60\u7684\u6743\u91cd\u3002<\/li>\n
      • estimatorerrors<\/em>\uff1a<\/strong>array\u7c7b\u578b\u3002\u6bcf\u4e2a\u5f31\u5b66\u4e60\u989d\u5206\u7c7b\u8bef\u5dee\u3002<\/li>\n
      • featureimportances<\/em>\uff1a<\/strong>array\u7c7b\u578b\u3002\u8fd4\u56de\u7279\u5f81\u91cd\u8981\u5ea6\u3002<\/li>\n<\/ul>\n

        \u65b9\u6cd5<\/h2>\n
          \n
        • decision_function(X)\uff1a<\/strong>\u8ba1\u7b97\u6837\u672cX\u7684\u51b3\u7b56\u51fd\u6570\u503c\u3002<\/li>\n
        • fit(X,y)\uff1a<\/strong>\u628a\u6570\u636e\u653e\u5165\u6a21\u578b\u4e2d\u8bad\u7ec3\u6a21\u578b\u3002<\/li>\n
        • get_params([deep])\uff1a<\/strong>\u8fd4\u56de\u6a21\u578b\u7684\u53c2\u6570\uff0c\u53ef\u4ee5\u7528\u4e8ePipeline\u4e2d\u3002<\/li>\n
        • predict(X)\uff1a<\/strong>\u9884\u6d4b\u6837\u672cX\u7684\u5206\u7c7b\u7c7b\u522b\u3002<\/li>\n
        • predict_log_proba(X)\uff1a<\/strong>\u8fd4\u56de\u6837\u672cX\u5728\u5404\u4e2a\u7c7b\u522b\u4e0a\u5bf9\u5e94\u7684\u5bf9\u6570\u6982\u7387\u3002<\/li>\n
        • predict_proba(X)\uff1a<\/strong>\u8fd4\u56de\u6837\u672cX\u5728\u5404\u4e2a\u7c7b\u522b\u4e0a\u5bf9\u5e94\u7684\u6982\u7387\u3002<\/li>\n
        • score(X,y[,sample_weight])\uff1a<\/strong>\u57fa\u4e8e\u62a5\u544a\u51b3\u5b9a\u7cfb\u6570$R^2$\u8bc4\u4f30\u6a21\u578b\u3002<\/li>\n
        • set_prams(**params)\uff1a<\/strong>\u521b\u5efa\u6a21\u578b\u53c2\u6570\u3002<\/li>\n
        • staged_decision_function(X)\uff1a<\/strong>\u8fd4\u56de\u6bcf\u4e2a\u9636\u6bb5\u6837\u672cX\u7684\u51b3\u7b56\u51fd\u6570\u503c\u3002<\/li>\n
        • staged_predict(X)\uff1a<\/strong>\u8fd4\u56de\u6bcf\u4e2a\u9636\u6bb5\u6837\u672cX\u7684\u9884\u6d4b\u503c\u3002<\/li>\n
        • staged_predict_proba(X)\uff1a<\/strong>\u8fd4\u56de\u6bcf\u4e2a\u9636\u6bb5\u6837\u672cX\u5728\u5404\u4e2a\u7c7b\u522b\u4e0a\u5bf9\u5e94\u7684\u6982\u7387\u3002<\/li>\n
        • staged_score(X,y[,sample_weight])\uff1a<\/strong>\u8fd4\u56de\u6bcf\u4e2a\u9636\u6bb5\u6837\u672cX\u7684$R^2$\u5206\u6570\u3002<\/li>\n<\/ul>\n

          AdaBoostRegressor<\/h1>\n

            AdaBoostRegressor<\/code>\u6a21\u578b\u548cAdaBoostClassfier<\/code>\u6a21\u578b\u53c2\u6570\u4e0a\u5dee\u4e0d\u591a\uff0c\u53ea\u662f\u524d\u8005\u4e00\u822c\u7528\u6765\u89e3\u51b3\u56de\u5f52\u95ee\u9898\uff0c\u540e\u8005\u7528\u6765\u89e3\u51b3\u5206\u7c7b\u95ee\u9898\uff0c\u9884\u6d4b\u503c\u5904\u7406\u65b9\u5f0f\u4e0d\u540c\u3002\u5e76\u4e14AdaBoostRegressor<\/code>\u6a21\u578b\u5728scikit-learn\u5e93\u4e2d\u53ea\u662f\u7528\u4e86Adaboost.R2\u7b97\u6cd5\u5b9e\u73b0\u3002<\/p>\n

            AdaBoostRegressor<\/code>\u6a21\u578b\u6ca1\u6709\u53c2\u6570’algorithm’\uff0c\u800c\u662f\u4f7f\u7528\u4e86loss<\/strong>\u53c2\u6570\uff0c\u5373\u8bef\u5dee\u51fd\u6570{‘linear’,’square’,’exponential’}\u7684\u9009\u62e9\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

          scikit-learn\u5e93\u4e4bAdaBoost\u7b97\u6cd5   \u5f53\u6211\u4eec\u5bf9Adaboost\u8c03\u53c2\u65f6\uff0c\u4e3b\u8981 […]<\/p>\n","protected":false},"author":3,"featured_media":3136,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[276,294,293],"tags":[],"_links":{"self":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3145"}],"collection":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3145"}],"version-history":[{"count":0,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3145\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/media\/3136"}],"wp:attachment":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3145"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3145"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3145"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}