{"id":65627,"date":"2026-01-25T13:25:29","date_gmt":"2026-01-25T05:25:29","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/65627.html"},"modified":"2026-01-25T13:25:29","modified_gmt":"2026-01-25T05:25:29","slug":"%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0-%e6%a2%af%e5%ba%a6%e6%8f%90%e5%8d%87%e6%a0%91","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/65627.html","title":{"rendered":"\u673a\u5668\u5b66\u4e60\u2014\u2014\u2014\u2014\u68af\u5ea6\u63d0\u5347\u6811"},"content":{"rendered":"<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u68af\u5ea6\u63d0\u5347\u6811&#xff08;GBDT&#xff09;\u662f\u5728\u51fd\u6570\u7a7a\u95f4\u4e2d\u901a\u8fc7\u68af\u5ea6\u4e0b\u964d\u6cd5\u4e32\u884c\u8bad\u7ec3\u591a\u68f5\u56de\u5f52\u51b3\u7b56\u6811&#xff0c;\u6bcf\u68f5\u65b0\u6811\u62df\u5408\u5f53\u524d\u6a21\u578b\u635f\u5931\u51fd\u6570\u7684\u8d1f\u68af\u5ea6&#xff0c;\u5e76\u901a\u8fc7\u5b66\u4e60\u7387\u63a7\u5236\u6bcf\u68f5\u6811\u7684\u8d21\u732e\u6743\u91cd&#xff0c;\u6700\u7ec8\u5c06\u6240\u6709\u6811\u7684\u9884\u6d4b\u7ed3\u679c\u52a0\u6743\u7d2f\u52a0&#xff0c;\u4ee5\u9010\u6b65\u6700\u5c0f\u5316\u635f\u5931\u51fd\u6570\u7684\u96c6\u6210\u5b66\u4e60\u7b97\u6cd5\u3002<\/p>\n<h3>\u4e00\u3001\u6838\u5fc3\u6982\u5ff5<\/h3>\n<h4>\u63d0\u5347&#xff08;Boosting&#xff09;<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5b9a\u4e49&#xff1a;\u4e32\u884c\u8bad\u7ec3\u591a\u4e2a\u5f31\u5b66\u4e60\u5668&#xff08;\u5982\u51b3\u7b56\u6811&#xff09;&#xff0c;\u6bcf\u4e00\u4e2a\u65b0\u5b66\u4e60\u5668\u90fd\u4fee\u6b63\u524d\u4e00\u4e2a\u7684\u9519\u8bef&#xff0c;\u6700\u7ec8\u96c6\u6210\u6240\u6709\u5b66\u4e60\u5668\u7684\u7ed3\u679c\u3002<\/p>\n<h4>\u5f31\u5b66\u4e60\u5668<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5b9a\u4e49&#xff1a;\u6027\u80fd\u7565\u4f18\u4e8e\u968f\u673a\u731c\u6d4b\u7684\u7b80\u5355\u6a21\u578b&#xff0c;\u5e76\u4e14GBDT \u4e2d\u56fa\u5b9a\u4e3a\u56de\u5f52\u51b3\u7b56\u6811\u3002<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u4f5c\u7528&#xff1a;\u5355\u68f5\u6811\u62df\u5408\u80fd\u529b\u5f31&#xff0c;\u4f46\u591a\u68f5\u6811\u7d2f\u52a0\u540e\u5f62\u6210\u5f3a\u5b66\u4e60\u5668\u3002<\/p>\n<h4>\u6b8b\u5dee<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5b9a\u4e49&#xff1a;\u771f\u5b9e\u503c &#8211; \u6a21\u578b\u5f53\u524d\u9884\u6d4b\u503c\u3002<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u4f5c\u7528&#xff1a;\u5e73\u65b9\u635f\u5931\u4e0b&#xff0c;\u6b8b\u5dee\u7b49\u4ef7\u4e8e\u635f\u5931\u51fd\u6570\u7684\u8d1f\u68af\u5ea6\u3002<\/p>\n<h4>\u68af\u5ea6\u63d0\u5347<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5b9a\u4e49&#xff1a;\u7528\u68af\u5ea6\u4e0b\u964d\u601d\u60f3\u4f18\u5316\u635f\u5931\u51fd\u6570&#xff0c;\u6bcf\u4e00\u8f6e\u6cbf\u635f\u5931\u51fd\u6570\u7684\u8d1f\u68af\u5ea6\u65b9\u5411\u8bad\u7ec3\u65b0\u5f31\u5b66\u4e60\u5668\u3002<\/p>\n<p>\u00a0 \u00a0 \u00a0 \u00a0 \u4f5c\u7528&#xff1a;\u6b8b\u5dee\u662f\u5e73\u65b9\u635f\u5931\u7684\u7279\u4f8b&#xff0c;\u68af\u5ea6\u63d0\u5347\u662f\u66f4\u901a\u7528\u7684\u6846\u67b6\u3002<\/p>\n<h4>\u5b66\u4e60\u7387<\/h4>\n<p>\u00a0 \u00a0 \u00a0 \u00a0 \u5b9a\u4e49&#xff1a;\u6bcf\u68f5\u5f31\u5b66\u4e60\u5668\u9884\u6d4b\u7ed3\u679c\u7684\u6743\u91cd\u7cfb\u6570&#xff08;\u03b7&#xff09;\u3002<\/p>\n<p>\u00a0 \u00a0 \u00a0 \u00a0 \u4f5c\u7528&#xff1a;\u63a7\u5236\u6bcf\u4e00\u8f6e\u4fee\u6b63\u7684\u5e45\u5ea6&#xff0c;\u9632\u6b62\u6a21\u578b\u8fc7\u62df\u5408\u3002<\/p>\n<h3>\u4e8c\u3001\u6570\u5b66\u539f\u7406<\/h3>\n<h4>1.\u8ba1\u7b97\u524d\u63d0<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u8bbe\u6709\u8bad\u7ec3\u96c6<img decoding=\"async\" alt=\"D&#061; \\\\left \\\\{ \\\\left ( x_{1},y_{1} \\\\right ) , \\\\left ( x_{2},y_{2} \\\\right )... \\\\left ( x_{n},y_{n} \\\\right )\\\\right \\\\}\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947bc750.png\" \/>,\u76ee\u6807\u662f\u5b66\u4e60\u4e00\u4e2a\u6a21\u578bF(x),\u6700\u5c0f\u5316\u635f\u5931\u51fd\u6570<img decoding=\"async\" alt=\"L\\\\left ( y,F\\\\left ( x \\\\right ) \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947cb179.png\" \/>\u3002<\/p>\n<p>GBDT \u7684\u6700\u7ec8\u6a21\u578b\u662f\u6240\u6709\u5f31\u5b66\u4e60\u5668\u7684\u52a0\u6743\u548c&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"F_{M}\\\\left ( x \\\\right )&#061;F_{0}\\\\left ( x \\\\right )&#043;\\\\sum_{m&#061;1}^{M}\\\\eta \\\\cdot h _{m}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947d647f.png\" \/><\/p>\n<ul>\n<li><img decoding=\"async\" alt=\"F_{0}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947e3891.png\" \/>&#xff1a;\u521d\u59cb\u6a21\u578b&#xff08;\u5e38\u6570&#xff0c;\u5982\u6807\u7b7e\u5747\u503c&#xff09;&#xff1b;<\/li>\n<li><img decoding=\"async\" alt=\"h_{m}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947ee17c.png\" \/>&#xff1a;\u7b2cm\u68f5\u56de\u5f52\u51b3\u7b56\u6811&#xff08;\u5f31\u5b66\u4e60\u5668&#xff09;&#xff1b;<\/li>\n<li>\u03b7&#xff1a;\u5b66\u4e60\u7387&#xff08;0&lt;\u03b7\u22641&#xff09;&#xff1b;<\/li>\n<li>M&#xff1a;\u5f31\u5b66\u4e60\u5668\u7684\u603b\u6570\u3002<\/li>\n<\/ul>\n<h4>2. \u6838\u5fc3\u63a8\u5bfc\u6b65\u9aa4<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0GBDT \u7684\u8fed\u4ee3\u8fc7\u7a0b\u672c\u8d28\u662f\u51fd\u6570\u7a7a\u95f4\u7684\u68af\u5ea6\u4e0b\u964d,\u666e\u901a\u68af\u5ea6\u4e0b\u964d\u662f\u53c2\u6570\u7a7a\u95f4\u7684\u4f18\u5316&#xff0c;GBDT \u662f\u4f18\u5316\u51fd\u6570\u3002<\/p>\n<h5>\u6b65\u9aa4 1&#xff1a;\u521d\u59cb\u5316\u521d\u59cb\u6a21\u578b<\/h5>\n<p>\u521d\u59cb\u6a21\u578b\u9009\u62e9\u4f7f\u635f\u5931\u51fd\u6570\u6700\u5c0f\u7684\u5e38\u6570&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"F_{0}\\\\left ( x \\\\right )&#061;argmin _{c}\\\\sum_{i&#061;1}^{m}L\\\\left ( y_{i},c \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a94803c81.png\" \/><\/p>\n<p>(\u6ce8&#xff1a;\u5b58\u5728\u5e73\u65b9\u635f\u5931\u548c\u7edd\u5bf9\u635f\u5931&#xff0c;\u8fd9\u91cc\u6709\u4ee5\u5e73\u65b9\u635f\u5931\u4e3a\u4f8b)<\/p>\n<h5>\u6b65\u9aa4 2&#xff1a;\u8fed\u4ee3\u8bad\u7ec3\u6bcf\u4e00\u68f5\u51b3\u7b56\u6811<\/h5>\n<p>1.\u8ba1\u7b97\u8d1f\u68af\u5ea6<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5bf9\u6bcf\u4e2a\u6837\u672ci&#xff0c;\u8ba1\u7b97\u635f\u5931\u51fd\u6570\u5728\u5f53\u524d\u6a21\u578b<img decoding=\"async\" alt=\"F_{m-1}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a94811369.png\" \/>\u5904\u7684\u8d1f\u68af\u5ea6&#xff0c;\u4f5c\u4e3a\u7b2cm\u68f5\u6811\u9700\u8981\u62df\u5408\u7684\u76ee\u6807\u3002<\/p>\n<p style=\"text-align:center\">\u516c\u5f0f\u4e3a&#xff1a;<img decoding=\"async\" alt=\"r_{im}&#061; -\\\\left [ \\\\frac{\\\\partial L\\\\left (y _{i},F\\\\left (x_{i} \\\\right ) \\\\right )}{\\\\partial F\\\\left ( x_{i} \\\\right )} \\\\right ]\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a9481b727.png\" \/><\/p>\n<p>2.\u62df\u5408\u56de\u5f52\u51b3\u7b56\u6811<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u7528\u8bad\u7ec3\u96c6<img decoding=\"async\" alt=\"\\\\left \\\\{ \\\\left ( x_{1} ,r_{1m}\\\\right ) ,\\\\left ( x_{2} ,r_{2m}\\\\right )...\\\\left ( x_{n} ,r_{nm}\\\\right )\\\\right \\\\}\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a94826820.png\" \/>\u00a0 \u8bad\u7ec3\u4e00\u68f5\u56de\u5f52\u51b3\u7b56\u6811<img decoding=\"async\" alt=\"h_{m}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052527-6975a947ee17c.png\" \/> hm\u200b(x)&#xff0c;\u5f97\u5230\u6811\u7684\u53f6\u8282\u70b9\u5212\u5206<img decoding=\"async\" alt=\"\\\\left \\\\{ R_{jm} \\\\right \\\\}\\\\binom{J}{j&#061;1}\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a94832ce1.png\" \/>,J\u662f\u53f6\u8282\u70b9\u6570&#xff09;\u3002<\/p>\n<p>3.\u66f4\u65b0\u53f6\u8282\u70b9\u6743\u91cd<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5bf9\u6bcf\u4e2a\u53f6\u8282\u70b9j&#xff0c;\u6c42\u89e3\u6700\u4f18\u6743\u91cd\u3002<\/p>\n<p style=\"text-align:center\">\u516c\u5f0f\u4e3a&#xff1a;<img decoding=\"async\" alt=\"C_{jm}&#061; argmin_{c}\\\\sum_{x_{i}\\\\epsilon R_{jm}}^{}L\\\\left ( y_{i},F_{m-1} \\\\left ( x_{i} \\\\right )&#043;\\\\eta \\\\cdot c\\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a9483e1ee.png\" \/>;<\/p>\n<p>4.\u66f4\u65b0\u6a21\u578b<\/p>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5c06\u7b2cm\u68f5\u6811\u7684\u7ed3\u679c\u52a0\u6743\u540e\u52a0\u5165\u6a21\u578b&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"F_{m}\\\\left ( x \\\\right )&#061; F_{m-1}\\\\left ( x \\\\right )&#043;\\\\eta \\\\cdot h_{m}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a9484c00b.png\" \/>;<\/p>\n<h5>\u6b65\u9aa4 3&#xff1a;\u7ec8\u6b62\u8fed\u4ee3<\/h5>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5f53\u8fed\u4ee3\u6b21\u6570\u8fbe\u5230M&#xff0c;\u6216\u635f\u5931\u51fd\u6570\u6536\u655b\u65f6&#xff0c;\u505c\u6b62\u8fed\u4ee3&#xff0c;\u5f97\u5230\u6700\u7ec8\u6a21\u578b <img decoding=\"async\" alt=\"F_{M}\\\\left ( x \\\\right )\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260125052528-6975a948643cb.png\" \/>\u3002<\/p>\n<h3>\u4e09\u3001\u4ee3\u7801\u89e3\u91ca\u2014\u2014\u4ee5\u56de\u5f52\u4efb\u52a1\u4e3a\u4f8b<\/h3>\n<h4>\u6a21\u5757\u4e00&#xff1a;\u5bfc\u5165\u6838\u5fc3\u5e93<\/h4>\n<p>import numpy as np  # \u6570\u503c\u8ba1\u7b97\u5e93&#xff0c;\u5904\u7406\u6570\u7ec4\/\u77e9\u9635\u8fd0\u7b97<br \/>\nimport pandas as pd  # \u6570\u636e\u5904\u7406\u5e93&#xff0c;\u7ed3\u6784\u5316\u6570\u636e\u7ba1\u7406<br \/>\nimport matplotlib.pyplot as plt  # \u53ef\u89c6\u5316\u5e93&#xff0c;\u7ed8\u5236\u56fe\u8868<br \/>\n# \u52a0\u8f7d\u52a0\u5dde\u623f\u4ef7\u6570\u636e\u96c6&#xff08;\u66ff\u4ee3\u6ce2\u58eb\u987f\u623f\u4ef7&#xff0c;\u89e3\u51b3sklearn\u7248\u672c\u517c\u5bb9\u95ee\u9898&#xff09;<br \/>\nfrom sklearn.datasets import fetch_california_housing<br \/>\n# \u5212\u5206\u8bad\u7ec3\u96c6\/\u6d4b\u8bd5\u96c6&#xff0c;\u8bc4\u4f30\u6a21\u578b\u6cdb\u5316\u80fd\u529b<br \/>\nfrom sklearn.model_selection import train_test_split<br \/>\n# GBDT\u56de\u5f52\u5668\u6838\u5fc3\u7c7b&#xff08;\u5c01\u88c5\u4e86GBDT\u7684\u5168\u90e8\u8fed\u4ee3\u903b\u8f91&#xff09;<br \/>\nfrom sklearn.ensemble import GradientBoostingRegressor<br \/>\n# \u56de\u5f52\u4efb\u52a1\u8bc4\u4f30\u6307\u6807&#xff1a;MSE(\u5747\u65b9\u8bef\u5dee)\u3001R\u00b2(\u51b3\u5b9a\u7cfb\u6570)<br \/>\nfrom sklearn.metrics import mean_squared_error, r2_score <\/p>\n<h4>\u6a21\u5757\u4e8c&#xff1a;\u6570\u636e\u51c6\u5907<\/h4>\n<p># \u52a0\u8f7d\u52a0\u5dde\u623f\u4ef7\u6570\u636e\u96c6&#xff1a;\u8fd4\u56de\u5b57\u5178\u5bf9\u8c61&#xff0c;\u5305\u542b\u7279\u5f81\u3001\u6807\u7b7e\u3001\u7279\u5f81\u540d\u7b49<br \/>\nhousing &#061; fetch_california_housing()<br \/>\n# \u5c06\u7279\u5f81\u6570\u7ec4\u8f6c\u4e3aDataFrame&#xff0c;\u6307\u5b9a\u5217\u540d&#xff08;\u65b9\u4fbf\u540e\u7eed\u7279\u5f81\u91cd\u8981\u6027\u5339\u914d&#xff09;<br \/>\n# housing.data: \u7279\u5f81\u6570\u7ec4(20640,8)&#xff1b;housing.feature_names: 8\u4e2a\u7279\u5f81\u540d\u79f0<br \/>\nX &#061; pd.DataFrame(housing.data, columns&#061;housing.feature_names)<br \/>\n# \u63d0\u53d6\u76ee\u6807\u53d8\u91cf&#xff08;\u623f\u4ef7&#xff0c;\u5355\u4f4d&#xff1a;10\u4e07\u7f8e\u5143&#xff09;<br \/>\ny &#061; housing.target<\/p>\n<p># \u5212\u5206\u8bad\u7ec3\u96c6(70%)\/\u6d4b\u8bd5\u96c6(30%)<br \/>\n# random_state&#061;42&#xff1a;\u56fa\u5b9a\u968f\u673a\u79cd\u5b50&#xff0c;\u4fdd\u8bc1\u6bcf\u6b21\u5212\u5206\u7ed3\u679c\u4e00\u81f4&#xff08;\u53ef\u590d\u73b0&#xff09;<br \/>\nX_train, X_test, y_train, y_test &#061; train_test_split(<br \/>\n    X, y, test_size&#061;0.3, random_state&#061;42<br \/>\n)<\/p>\n<h4>\u6a21\u5757\u4e09&#xff1a;\u6784\u5efaGBDT\u6a21\u578b<\/h4>\n<p># \u521d\u59cb\u5316GBDT\u56de\u5f52\u5668&#xff08;\u53c2\u6570\u5bf9\u5e94GBDT\u6570\u5b66\u539f\u7406&#xff09;<br \/>\ngbdt &#061; GradientBoostingRegressor(<br \/>\n    loss&#061;&#039;squared_error&#039;,    # \u635f\u5931\u51fd\u6570&#xff1a;\u5e73\u65b9\u635f\u5931&#xff08;\u56de\u5f52\u9ed8\u8ba4&#xff0c;\u4f2a\u6b8b\u5dee&#061;\u666e\u901a\u6b8b\u5dee&#xff09;<br \/>\n    learning_rate&#061;0.1,       # \u5b66\u4e60\u7387\u03b7&#xff1a;\u6bcf\u68f5\u6811\u7684\u8d21\u732e\u6743\u91cd&#xff08;\u6b65\u957f&#xff09;<br \/>\n    n_estimators&#061;100,        # \u6811\u7684\u6570\u91cfM&#xff1a;\u8fed\u4ee3100\u6b21&#xff08;\u8bad\u7ec3100\u68f5\u56de\u5f52\u6811&#xff09;<br \/>\n    max_depth&#061;3,             # \u5355\u68f5\u6811\u6700\u5927\u6df1\u5ea6&#xff1a;\u63a7\u5236\u8fc7\u62df\u5408&#xff08;GBDT\u5efa\u8bae3-5&#xff09;<br \/>\n    min_samples_split&#061;2,     # \u8282\u70b9\u5206\u88c2\u6700\u5c0f\u6837\u672c\u6570&#xff1a;&lt;2\u65f6\u505c\u6b62\u5206\u88c2<br \/>\n    random_state&#061;42          # \u56fa\u5b9a\u968f\u673a\u79cd\u5b50&#xff0c;\u4fdd\u8bc1\u6a21\u578b\u8bad\u7ec3\u8fc7\u7a0b\u53ef\u590d\u73b0<br \/>\n)<\/p>\n<p># \u8bad\u7ec3\u6a21\u578b&#xff1a;\u5e95\u5c42\u6267\u884cGBDT\u5b8c\u6574\u8fed\u4ee3\u6d41\u7a0b<br \/>\n# 1. \u521d\u59cb\u5316F0(x)&#061;\u8bad\u7ec3\u96c6\u6807\u7b7e\u5747\u503c&#xff1b;2. \u8fed\u4ee3100\u6b21\u62df\u5408\u4f2a\u6b8b\u5dee&#xff1b;3. \u7d2f\u52a0\u6240\u6709\u6811\u7ed3\u679c<br \/>\ngbdt.fit(X_train, y_train) <\/p>\n<h4>\u6a21\u5757\u56db&#xff1a;\u6a21\u578b\u8bc4\u4f30<\/h4>\n<p># \u7528\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u9884\u6d4b\u8bad\u7ec3\u96c6\/\u6d4b\u8bd5\u96c6\u623f\u4ef7<br \/>\ny_train_pred &#061; gbdt.predict(X_train)  # \u8bad\u7ec3\u96c6\u9884\u6d4b\u503c<br \/>\ny_test_pred &#061; gbdt.predict(X_test)    # \u6d4b\u8bd5\u96c6\u9884\u6d4b\u503c<\/p>\n<p># \u8ba1\u7b97\u8bc4\u4f30\u6307\u6807<br \/>\n# MSE(\u5747\u65b9\u8bef\u5dee)&#xff1a;\u8861\u91cf\u9884\u6d4b\u503c\u4e0e\u771f\u5b9e\u503c\u7684\u5e73\u5747\u5e73\u65b9\u504f\u5dee&#xff0c;\u8d8a\u5c0f\u8d8a\u597d<br \/>\ntrain_mse &#061; mean_squared_error(y_train, y_train_pred)  # \u8bad\u7ec3\u96c6MSE<br \/>\ntest_mse &#061; mean_squared_error(y_test, y_test_pred)    # \u6d4b\u8bd5\u96c6MSE<br \/>\n# R\u00b2(\u51b3\u5b9a\u7cfb\u6570)&#xff1a;\u8861\u91cf\u6a21\u578b\u89e3\u91ca\u6570\u636e\u53d8\u5f02\u7684\u80fd\u529b&#xff0c;\u8d8a\u63a5\u8fd11\u8d8a\u597d&#xff08;1&#061;\u5b8c\u7f8e\u62df\u5408&#xff0c;0&#061;\u7b49\u4ef7\u9884\u6d4b\u5747\u503c&#xff09;<br \/>\ntrain_r2 &#061; r2_score(y_train, y_train_pred)  # \u8bad\u7ec3\u96c6R\u00b2<br \/>\ntest_r2 &#061; r2_score(y_test, y_test_pred)    # \u6d4b\u8bd5\u96c6R\u00b2<\/p>\n<p># \u683c\u5f0f\u5316\u6253\u5370\u8bc4\u4f30\u7ed3\u679c&#xff08;\u4fdd\u75594\u4f4d\u5c0f\u6570&#xff0c;\u63d0\u5347\u53ef\u8bfb\u6027&#xff09;<br \/>\nprint(&#034;&#061;&#034;*50)<br \/>\nprint(f&#034;\u8bad\u7ec3\u96c6MSE: {train_mse:.4f} | \u8bad\u7ec3\u96c6R\u00b2: {train_r2:.4f}&#034;)<br \/>\nprint(f&#034;\u6d4b\u8bd5\u96c6MSE: {test_mse:.4f} | \u6d4b\u8bd5\u96c6R\u00b2: {test_r2:.4f}&#034;)<br \/>\nprint(&#034;&#061;&#034;*50) <\/p>\n<h4>\u6a21\u5757\u4e94&#xff1a;\u53ef\u89c6\u5316<\/h4>\n<p># &#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211; 5. \u53ef\u89c6\u5316&#xff1a;\u8bad\u7ec3\u8fc7\u7a0b\u8bef\u5dee\u53d8\u5316 &#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<br \/>\n# \u521d\u59cb\u5316\u6570\u7ec4&#xff1a;\u5b58\u50a8\u6bcf\u4e00\u8f6e\u8fed\u4ee3\u7684\u6d4b\u8bd5\u96c6MSE&#xff08;\u957f\u5ea6&#061;100&#xff0c;\u5bf9\u5e94100\u68f5\u6811&#xff09;<br \/>\ntest_score &#061; np.zeros((gbdt.n_estimators,), dtype&#061;np.float64)<br \/>\n# \u904d\u5386\u6bcf\u4e00\u8f6e\u8fed\u4ee3\u7684\u9884\u6d4b\u7ed3\u679c&#xff08;staged_predict\u8fd4\u56de\u6bcf\u8f6e\u7d2f\u52a0\u540e\u7684\u9884\u6d4b\u503c&#xff09;<br \/>\nfor i, y_pred in enumerate(gbdt.staged_predict(X_test)):<br \/>\n    # \u8ba1\u7b97\u7b2ci\u8f6e\u7684\u6d4b\u8bd5\u96c6MSE&#xff0c;\u5b58\u5165\u6570\u7ec4<br \/>\n    test_score[i] &#061; mean_squared_error(y_test, y_pred)<\/p>\n<p># \u521b\u5efa\u753b\u5e03<br \/>\nplt.figure(figsize&#061;(10, 6))<br \/>\n# \u7ed8\u5236\u8bad\u7ec3\u96c6\u8bef\u5dee\u66f2\u7ebf&#xff08;gbdt.train_score_\u662f\u5185\u7f6e\u5c5e\u6027&#xff0c;\u5b58\u50a8\u6bcf\u8f6e\u8bad\u7ec3\u96c6MSE&#xff09;<br \/>\nplt.plot(<br \/>\n    np.arange(gbdt.n_estimators) &#043; 1,  # x\u8f74&#xff1a;\u8fed\u4ee3\u6b21\u6570&#xff08;1-100&#xff09;<br \/>\n    gbdt.train_score_,                 # y\u8f74&#xff1a;\u8bad\u7ec3\u96c6\u6bcf\u8f6eMSE<br \/>\n    label&#061;&#039;\u8bad\u7ec3\u96c6MSE&#039;,                 # \u56fe\u4f8b\u6807\u7b7e<br \/>\n    color&#061;&#039;blue&#039;                       # \u66f2\u7ebf\u989c\u8272<br \/>\n)<br \/>\n# \u7ed8\u5236\u6d4b\u8bd5\u96c6\u8bef\u5dee\u66f2\u7ebf<br \/>\nplt.plot(<br \/>\n    np.arange(gbdt.n_estimators) &#043; 1,  # x\u8f74&#xff1a;\u8fed\u4ee3\u6b21\u6570&#xff08;1-100&#xff09;<br \/>\n    test_score,                        # y\u8f74&#xff1a;\u6d4b\u8bd5\u96c6\u6bcf\u8f6eMSE<br \/>\n    label&#061;&#039;\u6d4b\u8bd5\u96c6MSE&#039;,                 # \u56fe\u4f8b\u6807\u7b7e<br \/>\n    color&#061;&#039;red&#039;                        # \u66f2\u7ebf\u989c\u8272<br \/>\n)<br \/>\nplt.xlabel(&#039;\u8fed\u4ee3\u6b21\u6570&#xff08;\u6811\u7684\u6570\u91cfM&#xff09;&#039;)  # x\u8f74\u6807\u7b7e<br \/>\nplt.ylabel(&#039;\u5747\u65b9\u8bef\u5dee&#xff08;MSE&#xff09;&#039;)        # y\u8f74\u6807\u7b7e<br \/>\nplt.title(&#039;GBDT\u8bad\u7ec3\u8fc7\u7a0b\u8bef\u5dee\u53d8\u5316&#039;)    # \u56fe\u8868\u6807\u9898<br \/>\nplt.legend()  # \u663e\u793a\u56fe\u4f8b<br \/>\nplt.grid(alpha&#061;0.3)  # \u6dfb\u52a0\u7f51\u683c\u7ebf&#xff08;\u900f\u660e\u5ea60.3&#xff09;&#xff0c;\u65b9\u4fbf\u8bfb\u53d6\u5750\u6807<br \/>\nplt.tight_layout()  # \u81ea\u52a8\u8c03\u6574\u5e03\u5c40<br \/>\nplt.show()  # \u663e\u793a\u56fe\u8868 <\/p>\n<h4>\u7ed3\u8bed<\/h4>\n<p>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u611f\u8c22\u5927\u5bb6\u7684\u89c2\u770b&#xff01;\u5982\u6709\u4e0d\u8db3\u8bf7\u5927\u5bb6\u7684\u6279\u8bc4\u6307\u6b63\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u68af\u5ea6\u63d0\u5347\u6811&#xff08;GBDT&#xff09;\u662f\u5728\u51fd\u6570\u7a7a\u95f4\u4e2d\u901a\u8fc7\u68af\u5ea6\u4e0b\u964d\u6cd5\u4e32\u884c\u8bad\u7ec3\u591a\u68f5\u56de\u5f52\u51b3\u7b56\u6811&#xff0c;\u6bcf\u68f5\u65b0\u6811\u62df\u5408\u5f53\u524d\u6a21\u578b\u635f\u5931\u51fd\u6570\u7684\u8d1f\u68af\u5ea6&#xff0c;\u5e76\u901a\u8fc7\u5b66\u4e60\u7387\u63a7\u5236\u6bcf\u68f5\u6811\u7684\u8d21\u732e\u6743\u91cd&#xff0c;\u6700\u7ec8\u5c06\u6240\u6709\u6811\u7684\u9884\u6d4b\u7ed3\u679c\u52a0\u6743\u7d2f\u52a0&#xff0c;\u4ee5\u9010\u6b65\u6700\u5c0f\u5316\u635f\u5931\u51fd\u6570\u7684\u96c6\u6210\u5b66\u4e60\u7b97\u6cd5\u3002<br \/>\n\u4e00\u3001\u6838\u5fc3\u6982\u5ff5<br \/>\n\u63d0\u5347&#xff08;Boosting&#xff09; 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