“`\u53c2\u8003\u56de\u7b54\uff1a<\/p>\n
GBDT\u548cRF\u90fd\u662f\u96c6\u6210\u65b9\u6cd5\u4e2d\u7684\u7ecf\u5178\u6a21\u578b\uff0c\u6211\u4eec\u9700\u8981\u5f04\u6e05\u695a\u4e0b\u9762\u51e0\u4e2a\u95ee\u9898\uff1a1\uff09GBDT\u662f\u91c7\u7528boosing\u65b9\u6cd5\uff0cRF\u91c7\u7528\u7684\u662fbaggging\u65b9\u6cd5\uff1b2\uff09bias\u548cvariance\u662f\u89e3\u91ca\u6a21\u578b\u6cdb\u5316\u6027\u80fd\u7684\uff0c\u5176\u5b9e\u8fd8\u6709\u566a\u58f0\u3002<\/p>\n
\u7136\u540e\uff0c\u7406\u89e3GBDT\u548cRF\u6267\u884c\u539f\u7406\uff0c\u5176\u4e2dGBDT\u4e2d\u7684\u6838\u5fc3\u662f\u901a\u8fc7\u7528\u5206\u7c7b\u5668\uff08\u5982CART\u3001RF\uff09\u62df\u5408\u635f\u5931\u51fd\u6570\u68af\u5ea6\uff0c\u800c\u635f\u5931\u51fd\u6570\u7684\u5b9a\u4e49\u5c31\u51b3\u5b9a\u4e86\u5728\u5b50\u533a\u57df\u5185\u5404\u4e2a\u6b65\u957f\uff0c\u5176\u4e2d\u5c31\u662f\u671f\u671b\u8f93\u51fa\u4e0e\u5206\u7c7b\u5668\u9884\u6d4b\u8f93\u51fa\u7684\u67e5\uff0c\u5373bias\uff1b\u800cRF\u7684\u6838\u5fc3\u5c31\u662f\u81ea\u91c7\u6837\uff08\u6837\u672c\u968f\u673a\uff09\u548c\u5c5e\u6027\u968f\u673a\uff08\u6240\u6709\u6837\u672c\u4e2d\u968f\u673a\u9009\u62e9K\u4e2a\u5b50\u6837\u672c\u9009\u62e9\u6700\u4f18\u5c5e\u6027\u6765\u5212\u5206\uff09\uff0c\u6837\u672c\u6570\u76f8\u540c\u4e0b\u7684\u4e0d\u540c\u8bad\u7ec3\u96c6\u4ea7\u751f\u7684\u5404\u4e2a\u5206\u7c7b\u5668\uff0c\u5373\u6570\u636e\u7684\u6270\u52a8\u5bfc\u81f4\u6a21\u578b\u5b66\u4e60\u6027\u80fd\u7684\u53d8\u5316\uff0c\u5373variance\u3002<\/p>\n
Gradient boosting Decision Tree(GBDT)<\/p>\n
GB\u7b97\u6cd5\u4e2d\u6700\u5178\u578b\u7684\u57fa\u5b66\u4e60\u5668\u662f\u51b3\u7b56\u6811\uff0c\u5c24\u5176\u662fCART\uff0c\u6b63\u5982\u540d\u5b57\u7684\u542b\u4e49\uff0cGBDT\u662fGB\u548cDT\u7684\u7ed3\u5408\u3002\u8981\u6ce8\u610f\u7684\u662f\u8fd9\u91cc\u7684\u51b3\u7b56\u6811\u662f\u56de\u5f52\u6811\uff0cGBDT\u4e2d\u7684\u51b3\u7b56\u6811\u662f\u4e2a\u5f31\u6a21\u578b\uff0c\u6df1\u5ea6\u8f83\u5c0f\u4e00\u822c\u4e0d\u4f1a\u8d85\u8fc75\uff0c\u53f6\u5b50\u8282\u70b9\u7684\u6570\u91cf\u4e5f\u4e0d\u4f1a\u8d85\u8fc710\uff0c\u5bf9\u4e8e\u751f\u6210\u7684\u6bcf\u68f5\u51b3\u7b56\u6811\u4e58\u4e0a\u6bd4\u8f83\u5c0f\u7684\u7f29\u51cf\u7cfb\u6570\uff08\u5b66\u4e60\u7387<0.1\uff09\uff0c\u6709\u4e9bGBDT\u7684\u5b9e\u73b0\u52a0\u5165\u4e86\u968f\u673a\u62bd\u6837\uff08subsample 0.5<=f <=0.8\uff09\u63d0\u9ad8\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002\u901a\u8fc7\u4ea4\u53c9\u9a8c\u8bc1\u7684\u65b9\u6cd5\u9009\u62e9\u6700\u4f18\u7684\u53c2\u6570\u3002<\/p>\n
Random Forest\uff1a<\/p>\n
bagging \uff08\u4f60\u61c2\u5f97\uff0c\u539f\u672c\u53ebBootstrap aggregating\uff09\uff0cbagging \u7684\u5173\u952e\u662f\u91cd\u590d\u7684\u5bf9\u7ecf\u8fc7bootstrapped\u91c7\u6837\u6765\u7684\u89c2\u6d4b\u96c6\u5b50\u96c6\u8fdb\u884c\u62df\u5408\u3002\u7136\u540e\u6c42\u5e73\u5747\u3002\u3002\u3002\u4e00\u4e2abagged tree\u5145\u5206\u5229\u7528\u8fd12\/3\u7684\u6837\u672c\u96c6\u3002\u3002\u3002\u6240\u4ee5\u5c31\u6709\u4e86OOB\u9884\u4f30(outof bag estimation)<\/p>\n
GBDT\u548c\u968f\u673a\u68ee\u6797\u7684\u76f8\u540c\u70b9\uff1a<\/p>\n
1\uff09\u90fd\u662f\u7531\u591a\u68f5\u6811\u7ec4\u6210\uff1b2\uff09\u6700\u7ec8\u7684\u7ed3\u679c\u90fd\u662f\u7531\u591a\u68f5\u6811\u4e00\u8d77\u51b3\u5b9a<\/p>\n
GBDT\u548c\u968f\u673a\u68ee\u6797\u7684\u4e0d\u540c\u70b9\uff1a<\/p>\n
1\uff09\u7ec4\u6210\u968f\u673a\u68ee\u6797\u7684\u6811\u53ef\u4ee5\u662f\u5206\u7c7b\u6811\uff0c\u4e5f\u53ef\u4ee5\u662f\u56de\u5f52\u6811\uff1b\u800cGBDT\u53ea\u7531\u56de\u5f52\u6811\u7ec4\u6210\uff1b<\/p>\n
2\uff09\u7ec4\u6210\u968f\u673a\u68ee\u6797\u7684\u6811\u53ef\u4ee5\u5e76\u884c\u751f\u6210\uff1b\u800cGBDT\u53ea\u80fd\u662f\u4e32\u884c\u751f\u6210\uff1b<\/p>\n
3\uff09\u5bf9\u4e8e\u6700\u7ec8\u7684\u8f93\u51fa\u7ed3\u679c\u800c\u8a00\uff0c\u968f\u673a\u68ee\u6797\u91c7\u7528\u591a\u6570\u6295\u7968\u7b49\uff1b\u800cGBDT\u5219\u662f\u5c06\u6240\u6709\u7ed3\u679c\u7d2f\u52a0\u8d77\u6765\uff0c\u6216\u8005\u52a0\u6743\u7d2f\u52a0\u8d77\u6765\uff1b<\/p>\n
4\uff09\u968f\u673a\u68ee\u6797\u5bf9\u5f02\u5e38\u503c\u4e0d\u654f\u611f\uff0cGBDT\u5bf9\u5f02\u5e38\u503c\u975e\u5e38\u654f\u611f\uff1b<\/p>\n
5\uff09\u968f\u673a\u68ee\u6797\u5bf9\u8bad\u7ec3\u96c6\u4e00\u89c6\u540c\u4ec1\uff0cGBDT\u662f\u57fa\u4e8e\u6743\u503c\u7684\u5f31\u5206\u7c7b\u5668\u7684\u96c6\u6210\uff1b<\/p>\n
6\uff09\u968f\u673a\u68ee\u6797\u662f\u901a\u8fc7\u51cf\u5c11\u6a21\u578b\u65b9\u5dee\u63d0\u9ad8\u6027\u80fd\uff0cGBDT\u662f\u901a\u8fc7\u51cf\u5c11\u6a21\u578b\u504f\u5dee\u63d0\u9ad8\u6027\u80fd\u3002<\/p>\n
RF\u51b3\u7b56\u6811\uff1a<\/p>\n
\u5b66\u4e60\u968f\u673a\u68ee\u6797\u6a21\u578b\u524d\uff0c\u4e00\u5b9a\u8981\u5148\u4e86\u89e3\u51b3\u7b56\u6811\u6a21\u578b\u3002\u6811\u8d8a\u6df1\uff0c\u6a21\u578b\u8d8a\u590d\u6742\u3002<\/p>\n
\u51b3\u7b56\u6811\u6a21\u578b\u7684\u4f18\u70b9\u5982\u4e0b\u30021\uff09\u5bb9\u6613\u7406\u89e3\u548c\u89e3\u91ca\uff0c\u6811\u53ef\u4ee5\u88ab\u53ef\u89c6\u5316\u30022\uff09\u4e0d\u9700\u8981\u592a\u591a\u7684\u6570\u636e\u9884\u5904\u7406\u5de5\u4f5c\uff0c\u5373\u4e0d\u9700\u8981\u8fdb\u884c\u6570\u636e\u5f52\u4e00\u5316\uff0c\u521b\u9020\u54d1\u53d8\u91cf\u7b49\u64cd\u4f5c\u30023\uff09\u9690\u542b\u5730\u521b\u9020\u4e86\u591a\u4e2a\u8054\u5408\u7279\u5f81\uff0c\u5e76\u80fd\u591f\u89e3\u51b3\u975e\u7ebf\u6027\u95ee\u9898\u3002<\/p>\n
GBDT\u51b3\u7b56\u6811\uff1a<\/p>\n
\u8fed\u4ee3\u51b3\u7b56\u6811GBDT\uff08Gradient Boosting Decision Tree\uff09\u4e5f\u88ab\u79f0\u4e3a\u662fMART\uff08Multiple Additive Regression Tree)\uff09\u6216\u8005\u662fGBRT\uff08Gradient Boosting Regression Tree\uff09\uff0c\u4e5f\u662f\u4e00\u79cd\u57fa\u4e8e\u96c6\u6210\u601d\u60f3\u7684\u51b3\u7b56\u6811\u6a21\u578b\uff0c\u4f46\u662f\u5b83\u548cRandom Forest\u6709\u7740\u672c\u8d28\u4e0a\u7684\u533a\u522b\u3002\u4e0d\u5f97\u4e0d\u63d0\u7684\u662f\uff0cGBDT\u662f\u76ee\u524d\u7ade\u8d5b\u4e2d\u6700\u4e3a\u5e38\u7528\u7684\u4e00\u79cd\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u53ef\u4ee5\u9002\u7528\u4e8e\u591a\u79cd\u573a\u666f\uff0c\u66f4\u96be\u80fd\u53ef\u8d35\u7684\u662f\uff0cGBDT\u6709\u7740\u51fa\u4f17\u7684\u51c6\u786e\u7387\u3002<\/p>\n
\u6811\u7684\u526a\u679d\uff1a<\/p>\n
\uff081\uff09\u524d\u526a\u679d( Pre-Pruning)<\/p>\n
\u901a\u8fc7\u63d0\u524d\u505c\u6b62\u6811\u7684\u6784\u9020\u6765\u5bf9\u51b3\u7b56\u6811\u8fdb\u884c\u526a\u679d\uff0c\u4e00\u65e6\u505c\u6b62\u8be5\u8282\u70b9\u4e0b\u6811\u7684\u7ee7\u7eed\u6784\u9020\uff0c\u8be5\u8282\u70b9\u5c31\u6210\u4e86\u53f6\u8282\u70b9\u3002\u4e00\u822c\u6811\u7684\u524d\u526a\u679d\u539f\u5219\u6709\uff1aa.\u8282\u70b9\u8fbe\u5230\u5b8c\u5168\u7eaf\u5ea6\uff1bb.\u6811\u7684\u6df1\u5ea6\u8fbe\u5230\u7528\u6237\u6240\u8981\u7684\u6df1\u5ea6\uff1bc.\u8282\u70b9\u4e2d\u6837\u672c\u4e2a\u6570\u5c11\u4e8e\u7528\u6237\u6307\u5b9a\u4e2a\u6570\uff1bd.\u4e0d\u7eaf\u5ea6\u6307\u6807\u4e0b\u964d\u7684\u6700\u5927\u5e45\u5ea6\u5c0f\u4e8e\u7528\u6237\u6307\u5b9a\u7684\u5e45\u5ea6\u3002<\/p>\n
\uff082\uff09\u540e\u526a\u679d( Post-Pruning)<\/p>\n
<p>\u9996\u5148\u6784\u9020\u5b8c\u6574\u7684\u51b3\u7b56\u6811\uff0c\u5141\u8bb8\u51b3\u7b56\u6811\u8fc7\u5ea6\u62df\u5408\u8bad\u7ec3\u6570\u636e\uff0c\u7136\u540e\u5bf9\u90a3\u4e9b\u7f6e\u4fe1\u5ea6\u4e0d\u591f\u7684\u7ed3\u70b9\u7684\u5b50\u6811\u7528\u53f6\u7ed3\u70b9\u6765\u66ff\u4ee3\u3002CART \u91c7\u7528Cost-Complexity Pruning\uff08\u4ee3\u4ef7-\u590d\u6742\u5ea6\u526a\u679d\u6cd5\uff09\uff0c\u4ee3\u4ef7(cost) \uff1a\u4e3b\u8981\u6307\u6837\u672c\u9519\u5206\u7387\uff1b\u590d\u6742\u5ea6(complexity) \uff1a\u4e3b\u8981\u6307\u6811t\u7684\u53f6\u8282\u70b9\u6570\uff0c(Breiman\u2026)\u5b9a\u4e49\u6811t\u7684\u4ee3\u4ef7\u590d\u6742\u5ea6(cost-complexity):\u4fe1\u606f\u71b5H(X)\uff0c\u4fe1\u606f\u589e\u76ca=H(D)-H(Y|X)\uff0c\u4fe1\u606f\u589e\u76ca\u7387=gain(x)\/H(x)\uff0cGini\u7cfb\u6570=1-sum\uff08pk^2\uff09\uff0c\u57fa\u5c3c\u7cfb\u6570\u5c31\u662f\u71b5\u5728x=1\u7684\u5730\u65b9\u4e00\u9636\u6cf0\u52d2\u5c55\u5f00\u5f97\u5230f(x)=1-x\uff0c\u6240\u4ee5gini=sum[x(1-x)]=1-sum(x^2)\u3002<\/p>“`<\/p>\n","protected":false},"excerpt":{"rendered":"
“`\u53c2\u8003\u56de\u7b54\uff1a GBDT\u548cRF\u90fd\u662f\u96c6\u6210\u65b9\u6cd5\u4e2d\u7684\u7ecf\u5178\u6a21\u578b\uff0c\u6211\u4eec\u9700\u8981\u5f04\u6e05\u695a\u4e0b\u9762\u51e0\u4e2a\u95ee\u9898\uff1a1\uff09GBDT\u662f […]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101],"tags":[],"class_list":["post-45029","post","type-post","status-publish","format-standard","hentry","category-c"],"_links":{"self":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/45029","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/comments?post=45029"}],"version-history":[{"count":1,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/45029\/revisions"}],"predecessor-version":[{"id":45030,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/45029\/revisions\/45030"}],"wp:attachment":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/media?parent=45029"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/categories?post=45029"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/tags?post=45029"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}