{"id":2256,"date":"2023-07-23T01:36:42","date_gmt":"2023-07-23T01:36:42","guid":{"rendered":"https:\/\/statorials.org\/cn\/glm%e6%8b%9f%e5%90%88%e7%ae%97%e6%b3%95%e6%b2%a1%e6%9c%89%e6%94%b6%e6%95%9b\/"},"modified":"2023-07-23T01:36:42","modified_gmt":"2023-07-23T01:36:42","slug":"glm%e6%8b%9f%e5%90%88%e7%ae%97%e6%b3%95%e6%b2%a1%e6%9c%89%e6%94%b6%e6%95%9b","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/glm%e6%8b%9f%e5%90%88%e7%ae%97%e6%b3%95%e6%b2%a1%e6%9c%89%e6%94%b6%e6%95%9b\/","title":{"rendered":"\u5982\u4f55\u5904\u7406 r \u8b66\u544a\uff1aglm.fit\uff1a\u7b97\u6cd5\u672a\u6536\u655b"},"content":{"rendered":"

<\/p>\n

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\u60a8\u5728 R \u4e2d\u53ef\u80fd\u9047\u5230\u7684\u5e38\u89c1\u8b66\u544a\u662f\uff1a<\/span><\/p>\n

 glm.fit: algorithm did not converge\n<\/strong><\/span><\/pre>\n
\u5f53\u60a8\u5c1d\u8bd5\u5728 R \u4e2d\u62df\u5408\u903b\u8f91\u56de\u5f52\u6a21\u578b\u5e76\u770b\u5230\u5b8c\u7f8e\u5206\u79bb<\/strong>\uff08\u5373\u9884\u6d4b\u53d8\u91cf\u80fd\u591f\u5c06\u54cd\u5e94\u53d8\u91cf\u5b8c\u7f8e\u5206\u79bb\u4e3a 0 \u548c 1\uff09\u65f6\uff0c\u901a\u5e38\u4f1a\u51fa\u73b0\u6b64\u8b66\u544a\u3002<\/span><\/p>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u5904\u7406\u6b64\u8b66\u544a\u3002<\/span><\/p>\n
\u5982\u4f55\u91cd\u73b0\u8b66\u544a<\/strong><\/span><\/h3>\n
\u5047\u8bbe\u6211\u4eec\u5c1d\u8bd5\u5728 R \u4e2d\u62df\u5408\u4ee5\u4e0b\u903b\u8f91\u56de\u5f52\u6a21\u578b\uff1a<\/span><\/p>\n
 #create data frame<\/span>\ndf <- data. frame<\/span> (x=c(.1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1, 1.1, 1.3, 1.5, 1.7),\n                 y=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1))\n\n#attempt to fit logistic regression model\n<\/span>glm(y~x, data=df, family=\" binomial<\/span> \")\n\nCall: glm(formula = y ~ x, family = \"binomial\", data = df)\n\nCoefficients:\n(Intercept)x  \n     -409.1 431.1  \n\nDegrees of Freedom: 14 Total (ie Null); 13 Residual\nNull Deviance: 20.19 \nResidual Deviance: 2.468e-09 AIC: 4\nWarning messages:\n1: glm.fit: algorithm did not converge \n2: glm.fit: fitted probabilities numerically 0 or 1 occurred \n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u6211\u4eec\u6536\u5230\u8b66\u544a\u6d88\u606f\uff1a glm.fit\uff1a\u7b97\u6cd5\u6ca1\u6709\u6536\u655b<\/strong>\u3002<\/span><\/p>\n
\u6211\u4eec\u6536\u5230\u6b64\u6d88\u606f\u662f\u56e0\u4e3a\u9884\u6d4b\u53d8\u91cf x \u80fd\u591f\u5c06\u54cd\u5e94\u53d8\u91cf y \u5b8c\u7f8e\u5206\u79bb\u4e3a 0 \u548c 1\u3002<\/span><\/p>\n
\u8bf7\u6ce8\u610f\uff0c\u5bf9\u4e8e\u6bcf\u4e2a\u5c0f\u4e8e 1 \u7684 x \u503c\uff0cy \u7b49\u4e8e 0\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u7b49\u4e8e\u6216\u5927\u4e8e 1 \u7684 x \u503c\uff0cy \u7b49\u4e8e 1\u3002<\/span><\/p>\n
\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u9884\u6d4b\u53d8\u91cf\u65e0\u6cd5\u5c06\u54cd\u5e94\u53d8\u91cf\u5b8c\u7f8e\u5206\u79bb\u4e3a 0 \u548c 1 \u7684\u573a\u666f\uff1a<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (x=c(.1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1, 1.1, 1.3, 1.5, 1.7),\n                 y=c(0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1))\n\n#fit logistic regression model\n<\/span>glm(y~x, data=df, family=\" binomial<\/span> \")\n\nCall: glm(formula = y ~ x, family = \"binomial\", data = df)\n\nCoefficients:\n(Intercept) x  \n     -2.112 2.886  \n\nDegrees of Freedom: 14 Total (ie Null); 13 Residual\nNull Deviance: 20.73 \nResidual Deviance: 16.31 AIC: 20.31\n<\/span><\/span><\/strong><\/pre>\n
\u6211\u4eec\u6ca1\u6709\u6536\u5230\u4efb\u4f55\u8b66\u544a\u6d88\u606f\uff0c\u56e0\u4e3a\u9884\u6d4b\u53d8\u91cf\u65e0\u6cd5\u5b8c\u7f8e\u5730\u5c06\u54cd\u5e94\u53d8\u91cf\u5206\u4e3a 0 \u548c 1\u3002<\/span><\/p>\n
\u5982\u4f55\u5904\u7406\u8b66\u544a<\/strong><\/span><\/h3>\n
\u5982\u679c\u6211\u4eec\u9047\u5230\u5b8c\u7f8e\u5206\u79bb\u7684\u573a\u666f\uff0c\u6709\u4e24\u79cd\u5904\u7406\u65b9\u6cd5\uff1a<\/span><\/p>\n
\u65b9\u6cd5 1\uff1a\u4f7f\u7528\u60e9\u7f5a\u56de\u5f52\u3002<\/strong><\/span><\/p>\n
\u4e00\u79cd\u9009\u62e9\u662f\u4f7f\u7528\u60e9\u7f5a\u903b\u8f91\u56de\u5f52\u7684\u5f62\u5f0f\uff0c\u4f8b\u5982\u5957\u7d22\u903b\u8f91\u56de\u5f52\u6216\u5f39\u6027\u7f51\u7edc\u6b63\u5219\u5316\u3002<\/span><\/p>\n
\u6709\u5173\u5982\u4f55\u5728 R \u4e2d\u5b9e\u73b0\u60e9\u7f5a\u903b\u8f91\u56de\u5f52\u7684\u9009\u9879\uff0c\u8bf7\u53c2\u9605glmnet<\/a>\u5305\u3002<\/span><\/p>\n
\u65b9\u6cd52\uff1a\u4f7f\u7528\u9884\u6d4b\u53d8\u91cf\u5b8c\u7f8e\u9884\u6d4b\u54cd\u5e94\u53d8\u91cf\u3002<\/strong><\/span><\/p>\n
\u5982\u679c\u60a8\u6000\u7591\u603b\u4f53\u4e2d\u53ef\u80fd\u5b58\u5728\u8fd9\u79cd\u5b8c\u7f8e\u5206\u79bb\uff0c\u5219\u53ef\u4ee5\u7b80\u5355\u5730\u4f7f\u7528\u6b64\u9884\u6d4b\u53d8\u91cf\u6765\u5b8c\u7f8e\u9884\u6d4b\u54cd\u5e94\u53d8\u91cf\u7684\u503c\u3002<\/span><\/p>\n
\u4f8b\u5982\uff0c\u5728\u4e0a\u9762\u7684\u573a\u666f\u4e2d\uff0c\u6211\u4eec\u770b\u5230\u5f53\u9884\u6d4b\u53d8\u91cfx<\/strong>\u5c0f\u4e8e 1 \u65f6\uff0c\u54cd\u5e94\u53d8\u91cfy<\/strong>\u59cb\u7ec8\u7b49\u4e8e 0\u3002<\/span><\/p>\n
\u5982\u679c\u6211\u4eec\u6000\u7591\u8fd9\u79cd\u5173\u7cfb\u5728\u603b\u4f53\u4e2d\u6210\u7acb\uff0c\u6211\u4eec\u603b\u662f\u53ef\u4ee5\u9884\u6d4b\u5f53x<\/strong>\u5c0f\u4e8e 1 \u65f6y<\/strong>\u7684\u503c\u4e3a 0\uff0c\u5e76\u4e14\u4e0d\u7528\u62c5\u5fc3\u62df\u5408\u60e9\u7f5a\u903b\u8f91\u56de\u5f52\u6a21\u578b\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u6559\u7a0b\u63d0\u4f9b\u4e86\u6709\u5173\u5728 R \u4e2d\u4f7f\u7528glm()<\/strong>\u51fd\u6570\u7684\u66f4\u591a\u4fe1\u606f\uff1a<\/span><\/p>\n
 R\u4e2dglm\u548clm\u7684\u533a\u522b<\/a>
\u5982\u4f55\u5728 R \u4e2d\u4f7f\u7528 glm \u7684\u9884\u6d4b\u51fd\u6570<\/a>
\u5982\u4f55\u5904\u7406\uff1aglm.fit\uff1a\u6570\u503c\u8c03\u6574\u6982\u7387\u4e3a0\u62161\u53d1\u751f<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u5728 R \u4e2d\u53ef\u80fd\u9047\u5230\u7684\u5e38\u89c1\u8b66\u544a\u662f\uff1a glm.fit: algorithm did not converge \u5f53 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2256","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5904\u7406 R \u8b66\u544a\uff1aglm.fit\uff1a\u7b97\u6cd5\u5c1a\u672a\u6536\u655b - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5904\u7406 R \u4e2d\u7684\u4ee5\u4e0b\u8b66\u544a\u6d88\u606f\uff1aglm.fit\uff1a\u7b97\u6cd5\u5c1a\u672a\u6536\u655b\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/glm\u62df\u5408\u7b97\u6cd5\u6ca1\u6709\u6536\u655b\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u5904\u7406 R \u8b66\u544a\uff1aglm.fit\uff1a\u7b97\u6cd5\u5c1a\u672a\u6536\u655b - 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