{"id":38574,"date":"2025-05-20T17:43:21","date_gmt":"2025-05-20T09:43:21","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/38574.html"},"modified":"2025-05-20T17:43:21","modified_gmt":"2025-05-20T09:43:21","slug":"pythonai%e6%8f%90%e7%a4%ba%e8%af%8d%e7%b3%96%e5%b0%bf%e7%97%85%e9%a2%84%e6%b5%8b%e8%9e%8d%e5%90%88%e6%a8%a1%e5%9e%8b%ef%bc%9a%e4%bc%af%e5%8a%aa%e5%88%a9%e6%9c%b4%e7%b4%a0%e8%b4%9d%e5%8f%b6%e6%96%af","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/38574.html","title":{"rendered":"Python+AI\u63d0\u793a\u8bcd\u7cd6\u5c3f\u75c5\u9884\u6d4b\u878d\u5408\u6a21\u578b\uff1a\u4f2f\u52aa\u5229\u6734\u7d20\u8d1d\u53f6\u65af\u3001\u903b\u8f91\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u3001\u652f\u6301\u5411\u91cf\u673aSVM\u5e94\u7528"},"content":{"rendered":"

\u539f\u6587\u94fe\u63a5：\u00a0tecdat.cn\/?p=42054\u5206\u6790\u5e08：Yufei Fang<\/p>\n

<\/h5>\n

\u5728\u533b\u7597\u5065\u5eb7\u6570\u5b57\u5316\u8f6c\u578b\u6d6a\u6f6e\u4e2d，\u5982\u4f55\u5229\u7528\u6570\u636e\u79d1\u5b66\u6280\u672f\u63d0\u5347\u75be\u75c5\u9884\u6d4b\u7684\u7cbe\u51c6\u6027，\u6210\u4e3a\u4e34\u5e8a\u51b3\u7b56\u652f\u6301\u9886\u57df\u7684\u91cd\u8981\u8bfe\u9898\u3002\u672c\u6587\u6539\u7f16\u81ea\u4e3a\u67d0\u533b\u7597\u673a\u6784\u63d0\u4f9b\u7684\u54a8\u8be2\u9879\u76ee\u5b9e\u8df5，\u805a\u7126\u7cd6\u5c3f\u75c5\u60a3\u75c5\u98ce\u9669\u9884\u6d4b\u573a\u666f，\u901a\u8fc7\u6574\u5408\u591a\u5143\u6570\u636e\u5206\u6790\u4e0e\u673a\u5668\u5b66\u4e60\u6280\u672f，\u6784\u5efa\u517c\u5177\u79d1\u5b66\u6027\u4e0e\u4e34\u5e8a\u53ef\u89e3\u91ca\u6027\u7684\u9884\u6d4b\u6a21\u578b\u4f53\u7cfb\u3002（\u70b9\u51fb\u6587\u672b\u201c\u9605\u8bfb\u539f\u6587\u201d\u83b7\u53d6\u5b8c\u6574\u667a\u80fd\u4f53\u3001\u4ee3\u7801\u3001\u6570\u636e\u3001\u6587\u6863）\u3002<\/p>\n

\u7814\u7a76\u56e2\u961f\u57fa\u4e8e\u771f\u5b9e\u533b\u7597\u6570\u636e\u96c6，\u7cfb\u7edf\u5bf9\u6bd4\u4e86\u903b\u8f91\u56de\u5f52（LR）\u3001\u51b3\u7b56\u6811（DT）\u3001\u968f\u673a\u68ee\u6797（RF）\u3001\u652f\u6301\u5411\u91cf\u673a（SVM）\u548c\u4f2f\u52aa\u5229\u6734\u7d20\u8d1d\u53f6\u65af（BNB）\u7b49\u7b97\u6cd5\u7684\u8868\u73b0，\u5e76\u901a\u8fc7\u6a21\u578b\u878d\u5408\u6280\u672f\u5b9e\u73b0\u9884\u6d4b\u6027\u80fd\u7684\u8de8\u8d8a\u5f0f\u63d0\u5347\u3002\u4ece\u6570\u636e\u9884\u5904\u7406\u9636\u6bb5\u7684\u7279\u5f81\u5de5\u7a0b\u521b\u65b0，\u5230\u96c6\u6210\u5b66\u4e60\u7b56\u7565\u7684\u5e94\u7528，\u7814\u7a76\u5168\u7a0b\u8d2f\u7a7f\u201c\u533b\u7597\u95ee\u9898\u6570\u636e\u5316\u3001\u6570\u636e\u5904\u7406\u6d41\u7a0b\u5316\u3001\u6a21\u578b\u7ed3\u679c\u4e34\u5e8a\u5316\u201d\u7684\u601d\u8def\u3002\u6587\u4e2d\u5c55\u793a\u7684\u7279\u5f81\u76f8\u5173\u6027\u5206\u6790\u3001\u7b97\u6cd5\u8c03\u4f18\u65b9\u6cd5\u8bba\u53ca\u6a21\u578b\u878d\u5408\u6846\u67b6，\u5df2\u5728\u5b9e\u9645\u533b\u7597\u573a\u666f\u4e2d\u9a8c\u8bc1\u6709\u6548\u6027\u3002\u4e13\u9898\u9879\u76ee\u53ca\u667a\u80fd\u4f53\u6587\u4ef6\u5df2\u5206\u4eab\u5728\u4ea4\u6d41\u793e\u7fa4，\u9605\u8bfb\u539f\u6587\u8fdb\u7fa4\u548c500+\u884c\u4e1a\u4eba\u58eb\u5171\u540c\u4ea4\u6d41\u548c\u6210\u957f\u3002<\/p>\n

\u00a0\u6587\u7ae0\u8109\u7edc\u6d41\u7a0b\u56fe<\/h5>\n

<\/p>\n

\u7cd6\u5c3f\u75c5\u60a3\u75c5\u98ce\u9669\u9884\u6d4b：\u57fa\u4e8e\u591a\u7b97\u6cd5\u878d\u5408\u7684\u533b\u7597\u6570\u636e\u5efa\u6a21\u7814\u7a76<\/h5>\n
\u4e00\u3001\u6570\u636e\u9884\u5904\u7406\u4e0e\u7279\u5f81\u6316\u6398<\/h6>\n

\u672c\u7814\u7a76\u91c7\u7528\u67d0\u533b\u7597\u6570\u636e\u96c6（\u5305\u542b520\u6761\u6837\u672c\u300116\u9879\u7279\u5f81\u53d8\u91cf），\u6db5\u76d6\u5e74\u9f84\u3001\u6027\u522b\u53ca\u591a\u5c3f\u3001\u591a\u996e\u3001\u80a5\u80d6\u7b49\u4e34\u5e8a\u75c7\u72b6\u6307\u6807\u3002\u6570\u636e\u9884\u5904\u7406\u9700\u89e3\u51b3\u975e\u7ed3\u6784\u5316\u6570\u636e\u8f6c\u6362\u4e0e\u5173\u952e\u7279\u5f81\u8bc6\u522b\u4e24\u5927\u6838\u5fc3\u4efb\u52a1\u30021. \u6570\u636e\u6807\u51c6\u5316\u5904\u7406\u9488\u5bf9\u539f\u59cb\u6570\u636e\u4e2d\u7c7b\u522b\u578b\u7279\u5f81\u5360\u6bd4\u9ad8\u7684\u7279\u70b9，\u91c7\u7528\u6807\u7b7e\u7f16\u7801\u6280\u672f\u5b9e\u73b0\u6570\u636e\u5411\u91cf\u5316\u3002\u4ee5\u4e0b\u4e3a\u5173\u952e\u5b9e\u73b0\u4ee3\u7801（AI\u63d0\u793a\u8bcd：\u7528Python\u5bf9\u533b\u7597\u6570\u636e\u8fdb\u884c\u6807\u7b7e\u7f16\u7801，\u4fdd\u7559\u5e74\u9f84\u5b57\u6bb5，\u5176\u4f59\u7c7b\u522b\u7279\u5f81\u8f6c\u4e3a0-1\u6570\u503c）：<\/p>\n

ini
\n\u4f53\u9a8cAI\u4ee3\u7801\u52a9\u624b
\n\u4ee3\u7801\u89e3\u8bfb
\n\u590d\u5236\u4ee3\u7801
\n# \u5bfc\u5165\u6570\u636e\u5904\u7406\u5e93\u00a0
\nimport pandas as pd\u00a0
\nfrom sklearn.preprocessing import LabelEncoder\u00a0
\n# \u52a0\u8f7d\u6570\u636e\u96c6\u00a0
\nmedical_data\u00a0= pd.read_csv("diaataset.csv")\u00a0
\nencoder\u00a0= LabelEncoder()\u00a0
\n# \u5bf9\u975e\u5e74\u9f84\u7279\u5f81\u6267\u884c\u7f16\u7801\u00a0
\nfor column in medical_data.columns:\u00a0
\nif column != 'Age':\u00a0
\nmedical_data[column]\u00a0= encoder.fit_transform(medical_data[column]) <\/p>\n

\u5904\u7406\u540e\u7684\u6570\u636e\u7247\u6bb5\u5982\u56fe1\u6240\u793a，\u6240\u6709\u75c7\u72b6\u6307\u6807\u5747\u8f6c\u6362\u4e3a\u6570\u503c\u578b\u53d8\u91cf，\u4e3a\u540e\u7eed\u5efa\u6a21\u63d0\u4f9b\u6807\u51c6\u5316\u8f93\u5165\u3002<\/p>\n

<\/p>\n

2. \u7279\u5f81\u5173\u8054\u6027\u5206\u6790\u901a\u8fc7\u5224\u522b\u76f8\u5173\u7cfb\u6570\u5206\u6790\u7279\u5f81\u4e0e\u60a3\u75c5\u98ce\u9669\u7684\u5173\u8054\u6027，\u53d1\u73b0\u591a\u5c3f（Polyuria）\u548c\u591a\u996e（Polydipsia）\u7684\u6b63\u76f8\u5173\u6027\u6700\u5f3a，\u63d0\u793a\u8fd9\u4e24\u9879\u75c7\u72b6\u662f\u7cd6\u5c3f\u75c5\u7684\u6838\u5fc3\u9884\u8b66\u4fe1\u53f7；\u6027\u522b（Gender）\u5448\u73b0\u8d1f\u76f8\u5173，\u8868\u660e\u7537\u6027\u60a3\u75c5\u6982\u7387\u9ad8\u4e8e\u5973\u6027（\u56fe2）\u3002\u8fdb\u4e00\u6b65\u805a\u7126\u9633\u6027\u60a3\u8005\u7fa4\u4f53，\u5e74\u9f84\u5206\u5e03\u5448\u73b0\u660e\u663e\u89c4\u5f8b\u6027：35-60\u5c81\u4e3a\u9ad8\u53d1\u5e74\u9f84\u6bb5，\u4e14\u6bcf10\u5e74\u51fa\u73b0\u60a3\u75c5\u9ad8\u5cf0（\u56fe3）；\u6027\u522b\u5206\u5e03\u4e0a\u5973\u6027\u60a3\u8005\u5360\u6bd454%，\u4f46\u7537\u6027\u60a3\u8005\u5e73\u5747\u5e74\u9f84\u66f4\u9ad8，\u6697\u793a\u5973\u6027\u60a3\u75c5\u5e74\u9f84\u53ef\u80fd\u66f4\u65e9（\u56fe4\u3001\u56fe5）\u3002<\/p>\n

<\/p>\n

<\/p>\n

<\/p>\n

<\/p>\n

\u4e8c\u3001\u57fa\u7840\u6a21\u578b\u6784\u5efa\u4e0e\u6027\u80fd\u6f14\u8fdb<\/h6>\n

\u7814\u7a76\u9009\u53d65\u79cd\u7ecf\u5178\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u6784\u5efa\u9884\u6d4b\u6a21\u578b，\u901a\u8fc7\u4ea4\u53c9\u9a8c\u8bc1\u4e0e\u53c2\u6570\u8c03\u4f18，\u9010\u6b65\u6316\u6398\u7b97\u6cd5\u6f5c\u529b\u30021. \u903b\u8f91\u56de\u5f52（LR）：\u7ebf\u6027\u6982\u7387\u5efa\u6a21\u7684\u57fa\u51c6\u903b\u8f91\u56de\u5f52\u901a\u8fc7Sigmoid\u51fd\u6570\u5c06\u7ebf\u6027\u7ec4\u5408\u8f6c\u6362\u4e3a\u60a3\u75c5\u6982\u7387，\u516c\u5f0f\u4e3a：<\/p>\n

<\/p>\n

\u5176\u4e2d，(w_i)\u4e3a\u7279\u5f81\u6743\u91cd，\u53cd\u6620\u75c7\u72b6\u5bf9\u60a3\u75c5\u98ce\u9669\u7684\u5f71\u54cd\u7a0b\u5ea6\u3002\u521d\u59cb\u6a21\u578b\u6d4b\u8bd5\u96c6\u51c6\u786e\u7387\u4e3a93.27%，\u7ecf\u7f51\u683c\u641c\u7d22\u8c03\u4f18（AI\u63d0\u793a\u8bcd：\u7528\u7f51\u683c\u641c\u7d22\u4f18\u5316\u903b\u8f91\u56de\u5f52\u6b63\u5219\u5316\u53c2\u6570，\u63d0\u5347\u533b\u7597\u5206\u7c7b\u6a21\u578b\u51c6\u786e\u7387），\u786e\u5b9a\u6700\u4f18\u53c2\u6570\u4e3aC=1\u3001solver=\u2018saga\u2019，\u8c03\u4f18\u540e\u6a21\u578b\u5bf9\u591a\u5c3f\u3001\u591a\u996e\u7684\u6b63\u5411\u6743\u91cd\u663e\u8457\u589e\u5f3a（\u56fe6）\u3002<\/p>\n

<\/p>\n

2. \u51b3\u7b56\u6811（DT）：\u89c4\u5219\u5316\u5efa\u6a21\u7684\u76f4\u89c2\u8868\u8fbe\u51b3\u7b56\u6811\u901a\u8fc7\u57fa\u5c3c\u7cfb\u6570\u9012\u5f52\u5212\u5206\u7279\u5f81，\u5f62\u6210\u53ef\u89e3\u91ca\u7684\u5206\u7c7b\u89c4\u5219\u3002\u521d\u59cb\u6a21\u578b\u6d4b\u8bd5\u96c6\u51c6\u786e\u7387\u8fbe95.2%，\u7f51\u683c\u641c\u7d22\u663e\u793a\u9ed8\u8ba4\u53c2\u6570（\u57fa\u5c3c\u7cfb\u6570\u5212\u5206\u3001\u65e0\u6df1\u5ea6\u9650\u5236）\u5373\u8fbe\u6700\u4f18\u6027\u80fd，\u7279\u5f81\u91cd\u8981\u6027\u6392\u5e8f\u663e\u793a\u591a\u5c3f\u3001\u6027\u522b\u3001\u5e74\u9f84\u4e3a\u524d\u4e09\u5927\u5f71\u54cd\u56e0\u7d20（\u56fe7）\u3002<\/p>\n

<\/p>\n

3. \u968f\u673a\u68ee\u6797（RF）：\u96c6\u6210\u5b66\u4e60\u7684\u6027\u80fd\u7a81\u7834\u968f\u673a\u68ee\u6797\u901a\u8fc7\u81ea\u52a9\u91c7\u6837\u548c\u968f\u673a\u7279\u5f81\u9009\u62e9\u6784\u5efa\u591a\u68f5\u51b3\u7b56\u6811，\u4ee5\u6295\u7968\u673a\u5236\u63d0\u5347\u9884\u6d4b\u9c81\u68d2\u6027\u3002\u8be5\u6a21\u578b\u65e0\u9700\u590d\u6742\u8c03\u4f18\u5373\u8fbe99.04%\u7684\u6d4b\u8bd5\u96c6\u51c6\u786e\u7387，\u7279\u5f81\u91cd\u8981\u6027\u5206\u5e03\u4e0e\u903b\u8f91\u56de\u5f52\u3001\u51b3\u7b56\u6811\u9ad8\u5ea6\u4e00\u81f4，\u518d\u6b21\u9a8c\u8bc1\u6838\u5fc3\u75c7\u72b6\u7684\u5173\u952e\u4f5c\u7528（\u56fe8\u3001\u56fe9）\u3002<\/p>\n

<\/p>\n

<\/p>\n

\n

\u70b9\u51fb\u6807\u9898\u67e5\u9605\u5f80\u671f\u5185\u5bb9<\/p>\n

\"\u56fe\u7247\"<\/p>\n

\u9ad8\u7ef4\u53d8\u91cf\u9009\u62e9\u4e13\u9898|R\u3001Python\u7528HOLP\u3001Lasso\u3001SCAD\u3001PCR\u3001ElasticNet\u5b9e\u4f8b\u5408\u96c6\u5206\u6790\u4f01\u4e1a\u8d22\u52a1\u3001\u7cd6\u5c3f\u75c5<\/p>\n

<\/p>\n

\u5de6\u53f3\u6ed1\u52a8\u67e5\u770b\u66f4\u591a<\/p>\n

<\/p>\n

01<\/p>\n

\"\u56fe\u7247\"<\/p>\n

02<\/p>\n

\"\u56fe\u7247\"<\/p>\n

03<\/p>\n

\"\u56fe\u7247\"<\/p>\n

04<\/p>\n

\"\u56fe\u7247\"<\/p>\n

4. \u652f\u6301\u5411\u91cf\u673a（SVM）：\u975e\u7ebf\u6027\u6a21\u5f0f\u7684\u6355\u6349\u539f\u59cbSVM\u6a21\u578b（\u7ebf\u6027\u6838）\u51c6\u786e\u7387\u4ec568%，\u7ecf\u7f51\u683c\u641c\u7d22\u4f18\u5316（AI\u63d0\u793a\u8bcd：\u7528RBF\u6838\u548c\u7f51\u683c\u641c\u7d22\u63d0\u5347SVM\u5728\u533b\u7597\u6570\u636e\u4e2d\u7684\u5206\u7c7b\u6027\u80fd），\u9009\u5b9aC=100\u3001gamma=0.1，\u51c6\u786e\u7387\u63d0\u5347\u81f397%，\u8868\u660e\u975e\u7ebf\u6027\u6838\u51fd\u6570\u80fd\u6709\u6548\u6316\u6398\u7279\u5f81\u95f4\u590d\u6742\u5173\u8054（\u56fe10\u3001\u56fe11）\u3002<\/p>\n

<\/p>\n

<\/p>\n

5. \u4f2f\u52aa\u5229\u6734\u7d20\u8d1d\u53f6\u65af（BNB）：\u6982\u7387\u72ec\u7acb\u5047\u8bbe\u4e0b\u7684\u5efa\u6a21\u8be5\u6a21\u578b\u57fa\u4e8e\u7279\u5f81\u6761\u4ef6\u72ec\u7acb\u5047\u8bbe，\u4ea4\u53c9\u9a8c\u8bc1\u5e73\u5747\u51c6\u786e\u738788.69%，\u7565\u4f4e\u4e8e\u5176\u4ed6\u6a21\u578b，\u63a8\u6d4b\u533b\u7597\u7279\u5f81\u95f4\u5b9e\u9645\u5173\u8054\u6027\u4e0e\u72ec\u7acb\u5047\u8bbe\u5b58\u5728\u5dee\u5f02（\u56fe12）\u3002<\/p>\n

<\/p>\n

\u4e09\u3001\u6a21\u578b\u878d\u5408：\u4ece\u5355\u4e00\u7b97\u6cd5\u5230\u7efc\u5408\u51b3\u7b56<\/h6>\n

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  • \u7279\u5f81\u5de5\u7a0b\u7684\u57fa\u7840\u6027\u4f5c\u7528\n

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  • \u96c6\u6210\u5b66\u4e60\u7684\u663e\u8457\u4f18\u52bf\n

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    <\/h5>\n

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    <\/p>\n

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    <\/p>\n

    \n

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    <\/p>\n

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    \u672c\u6587\u9009\u81ea\u300aPython+AI\u63d0\u793a\u8bcd\u7cd6\u5c3f\u75c5\u9884\u6d4b\u6a21\u578b\u878d\u5408\u6784\u5efa：\u4f2f\u52aa\u5229\u6734\u7d20\u8d1d\u53f6\u65af\u3001\u903b\u8f91\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u3001\u652f\u6301\u5411\u91cf\u673aSVM\u5e94\u7528\u300b\u3002<\/p>\n

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    \u8bfe\u7a0b\u89c6\u9891|R\u8bed\u8a00bnlearn\u5305：\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u6784\u9020\u53ca\u53c2\u6570\u5b66\u4e60\u7684\u539f\u7406\u548c\u5b9e\u4f8b<\/p>\n

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    python\u8d1d\u53f6\u65af\u968f\u673a\u8fc7\u7a0b：\u9a6c\u5c14\u53ef\u592b\u94feMarkov-Chain，MC\u548cMetropolis-Hastings，MH\u91c7\u6837\u7b97\u6cd5\u53ef\u89c6\u5316<\/p>\n

    Python\u8d1d\u53f6\u65af\u63a8\u65adMetropolis-Hastings（M-H）MCMC\u91c7\u6837\u7b97\u6cd5\u7684\u5b9e\u73b0<\/p>\n

    Metropolis Hastings\u91c7\u6837\u548c\u8d1d\u53f6\u65af\u6cca\u677e\u56de\u5f52Poisson\u6a21\u578b<\/p>\n

    Matlab\u7528BUGS\u9a6c\u5c14\u53ef\u592b\u533a\u5236\u8f6c\u6362Markov switching\u968f\u673a\u6ce2\u52a8\u7387\u6a21\u578b\u3001\u5e8f\u5217\u8499\u7279\u5361\u7f57SMC\u3001M H\u91c7\u6837\u5206\u6790\u65f6\u95f4\u5e8f\u5217<\/p>\n

    R\u8bed\u8a00RSTAN MCMC：NUTS\u91c7\u6837\u7b97\u6cd5\u7528LASSO \u6784\u5efa\u8d1d\u53f6\u65af\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u5206\u6790\u804c\u4e1a\u58f0\u671b\u6570\u636e<\/p>\n

    R\u8bed\u8a00BUGS\u5e8f\u5217\u8499\u7279\u5361\u7f57SMC\u3001\u9a6c\u5c14\u53ef\u592b\u8f6c\u6362\u968f\u673a\u6ce2\u52a8\u7387SV\u6a21\u578b\u3001\u7c92\u5b50\u6ee4\u6ce2\u3001Metropolis Hasting\u91c7\u6837\u65f6\u95f4\u5e8f\u5217\u5206\u6790<\/p>\n

    R\u8bed\u8a00Metropolis Hastings\u91c7\u6837\u548c\u8d1d\u53f6\u65af\u6cca\u677e\u56de\u5f52Poisson\u6a21\u578b<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65afMCMC：\u7528rstan\u5efa\u7acb\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u5206\u6790\u6c7d\u8f66\u6570\u636e\u548c\u53ef\u89c6\u5316\u8bca\u65ad<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65afMCMC：GLM\u903b\u8f91\u56de\u5f52\u3001Rstan\u7ebf\u6027\u56de\u5f52\u3001Metropolis Hastings\u4e0eGibbs\u91c7\u6837\u7b97\u6cd5\u5b9e\u4f8b<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65afPoisson\u6cca\u677e-\u6b63\u6001\u5206\u5e03\u6a21\u578b\u5206\u6790\u804c\u4e1a\u8db3\u7403\u6bd4\u8d5b\u8fdb\u7403\u6570<\/p>\n

    R\u8bed\u8a00\u7528Rcpp\u52a0\u901fMetropolis-Hastings\u62bd\u6837\u4f30\u8ba1\u8d1d\u53f6\u65af\u903b\u8f91\u56de\u5f52\u6a21\u578b\u7684\u53c2\u6570<\/p>\n

    R\u8bed\u8a00\u903b\u8f91\u56de\u5f52\u3001Naive Bayes\u8d1d\u53f6\u65af\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u7b97\u6cd5\u9884\u6d4b\u5fc3\u810f\u75c5<\/p>\n

    R\u8bed\u8a00\u4e2d\u8d1d\u53f6\u65af\u7f51\u7edc（BN）\u3001\u52a8\u6001\u8d1d\u53f6\u65af\u7f51\u7edc\u3001\u7ebf\u6027\u6a21\u578b\u5206\u6790\u9519\u988c\u7578\u5f62\u6570\u636e<\/p>\n

    R\u8bed\u8a00\u4e2d\u7684block Gibbs\u5409\u5e03\u65af\u91c7\u6837\u8d1d\u53f6\u65af\u591a\u5143\u7ebf\u6027\u56de\u5f52<\/p>\n

    Python\u8d1d\u53f6\u65af\u56de\u5f52\u5206\u6790\u4f4f\u623f\u8d1f\u62c5\u80fd\u529b\u6570\u636e\u96c6<\/p>\n

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    Python\u7528PyMC3\u5b9e\u73b0\u8d1d\u53f6\u65af\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/p>\n

    R\u8bed\u8a00\u7528WinBUGS \u8f6f\u4ef6\u5bf9\u5b66\u672f\u80fd\u529b\u6d4b\u9a8c\u5efa\u7acb\u5c42\u6b21（\u5206\u5c42）\u8d1d\u53f6\u65af\u6a21\u578b<\/p>\n

    R\u8bed\u8a00Gibbs\u62bd\u6837\u7684\u8d1d\u53f6\u65af\u7b80\u5355\u7ebf\u6027\u56de\u5f52\u4eff\u771f\u5206\u6790<\/p>\n

    R\u8bed\u8a00\u548cSTAN,JAGS：\u7528RSTAN,RJAG\u5efa\u7acb\u8d1d\u53f6\u65af\u591a\u5143\u7ebf\u6027\u56de\u5f52\u9884\u6d4b\u9009\u4e3e\u6570\u636e<\/p>\n

    R\u8bed\u8a00\u57fa\u4e8ecopula\u7684\u8d1d\u53f6\u65af\u5206\u5c42\u6df7\u5408\u6a21\u578b\u7684\u8bca\u65ad\u51c6\u786e\u6027\u7814\u7a76<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65af\u7ebf\u6027\u56de\u5f52\u548c\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6784\u5efa\u5de5\u8d44\u9884\u6d4b\u6a21\u578b<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65af\u63a8\u65ad\u4e0eMCMC：\u5b9e\u73b0Metropolis-Hastings \u91c7\u6837\u7b97\u6cd5\u793a\u4f8b<\/p>\n

    R\u8bed\u8a00stan\u8fdb\u884c\u57fa\u4e8e\u8d1d\u53f6\u65af\u63a8\u65ad\u7684\u56de\u5f52\u6a21\u578b<\/p>\n

    R\u8bed\u8a00\u4e2dRStan\u8d1d\u53f6\u65af\u5c42\u6b21\u6a21\u578b\u5206\u6790\u793a\u4f8b<\/p>\n

    R\u8bed\u8a00\u4f7f\u7528Metropolis-Hastings\u91c7\u6837\u7b97\u6cd5\u81ea\u9002\u5e94\u8d1d\u53f6\u65af\u4f30\u8ba1\u4e0e\u53ef\u89c6\u5316<\/p>\n

    R\u8bed\u8a00\u968f\u673a\u641c\u7d22\u53d8\u91cf\u9009\u62e9SSVS\u4f30\u8ba1\u8d1d\u53f6\u65af\u5411\u91cf\u81ea\u56de\u5f52（BVAR）\u6a21\u578b<\/p>\n

    WinBUGS\u5bf9\u591a\u5143\u968f\u673a\u6ce2\u52a8\u7387\u6a21\u578b：\u8d1d\u53f6\u65af\u4f30\u8ba1\u4e0e\u6a21\u578b\u6bd4\u8f83<\/p>\n

    R\u8bed\u8a00\u5b9e\u73b0MCMC\u4e2d\u7684Metropolis\u2013Hastings\u7b97\u6cd5\u4e0e\u5409\u5e03\u65af\u91c7\u6837<\/p>\n

    R\u8bed\u8a00\u8d1d\u53f6\u65af\u63a8\u65ad\u4e0eMCMC：\u5b9e\u73b0Metropolis-Hastings \u91c7\u6837\u7b97\u6cd5\u793a\u4f8b<\/p>\n

    R\u8bed\u8a00\u4f7f\u7528Metropolis-Hastings\u91c7\u6837\u7b97\u6cd5\u81ea\u9002\u5e94\u8d1d\u53f6\u65af\u4f30\u8ba1\u4e0e\u53ef\u89c6\u5316<\/p>\n

    \u89c6\u9891：R\u8bed\u8a00\u4e2d\u7684Stan\u6982\u7387\u7f16\u7a0bMCMC\u91c7\u6837\u7684\u8d1d\u53f6\u65af\u6a21\u578b<\/p>\n

    R\u8bed\u8a00MCMC:Metropolis-Hastings\u91c7\u6837\u7528\u4e8e\u56de\u5f52\u7684\u8d1d\u53f6\u65af\u4f30\u8ba1<\/p>\n

    <\/p>\n

    <\/p>\n

    <\/p>\n

    <\/p>\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

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