{"id":189376,"date":"2024-05-09T17:34:22","date_gmt":"2024-05-09T09:34:22","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189376.html"},"modified":"2024-05-09T17:34:26","modified_gmt":"2024-05-09T09:34:26","slug":"%e5%ae%8c%e5%85%a8%e9%9b%b6%e5%9f%ba%e7%a1%80%e5%ad%a6%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e7%9a%84%e8%af%9d%ef%bc%8c%e8%bf%98%e9%9c%80%e8%a6%81%e6%8e%8c%e6%8f%a1%e5%93%aa%e4%ba%9b%e7%9f%a5%e8%af%86","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189376.html","title":{"rendered":"\u5b8c\u5168\u96f6\u57fa\u7840\u5b66\u673a\u5668\u5b66\u4e60\u7684\u8bdd\uff0c\u8fd8\u9700\u8981\u638c\u63e1\u54ea\u4e9b\u77e5\u8bc6"},"content":{"rendered":"<p style=\"text-align:center\"><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/26095333\/9feb8aa7-e385-453e-86a8-9e8af22ea2d5.webp\" alt=\"\u5b8c\u5168\u96f6\u57fa\u7840\u5b66\u673a\u5668\u5b66\u4e60\u7684\u8bdd\uff0c\u8fd8\u9700\u8981\u638c\u63e1\u54ea\u4e9b\u77e5\u8bc6\" \/><\/p>\n<p><p><a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u662f\u4e00\u95e8\u96c6\u6570\u5b66\u3001\u7edf\u8ba1\u5b66\u3001\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u9886\u57df\u77e5\u8bc6\u4e3a\u4e00\u4f53\u7684\u5b66\u79d1\u3002<strong>\u8981\u4ece\u5b8c\u5168\u96f6\u57fa\u7840\u5b66\u8d77\u673a\u5668\u5b66\u4e60\uff0c\u9700\u8981\u638c\u63e1\u7684\u77e5\u8bc6\u5305\u62ec\u6570\u5b66\u548c\u7edf\u8ba1\u5b66\u57fa\u7840\u3001\u7f16\u7a0b\u8bed\u8a00\u6280\u80fd\u3001\u6570\u636e\u5904\u7406\u4e0e\u5206\u6790\u80fd\u529b\u3001\u673a\u5668\u5b66\u4e60\u7406\u8bba\u4e0e\u7b97\u6cd5\u3001\u5b9e\u8df5\u5e94\u7528\u4e0e\u9879\u76ee\u7ecf\u9a8c<\/strong>\u3002\u9996\u5148\uff0c\u6570\u5b66\u548c\u7edf\u8ba1\u5b66\u57fa\u7840\u662f\u673a\u5668\u5b66\u4e60\u4e2d\u6700\u91cd\u8981\u7684\u5de5\u5177\uff0c\u5176\u4e2d\u7ebf\u6027\u4ee3\u6570\u3001\u6982\u7387\u8bba\u4e0e\u6570\u7406\u7edf\u8ba1\u3001\u5fae\u79ef\u5206\u3001\u6700\u4f18\u5316\u7406\u8bba\u662f\u5fc5\u4e0d\u53ef\u5c11\u7684\u6570\u5b66\u57fa\u7840\u3002\u5728\u6b64\u57fa\u7840\u4e0a\uff0c\u7f16\u7a0b\u8bed\u8a00\u6280\u80fd\u4e5f\u975e\u5e38\u5173\u952e\uff0cPython \u662f\u6700\u53d7\u6b22\u8fce\u7684\u673a\u5668\u5b66\u4e60\u7f16\u7a0b\u8bed\u8a00\u4e4b\u4e00\uff0c\u5b83\u62e5\u6709\u4e30\u5bcc\u7684\u5e93\u548c\u6846\u67b6\uff0c\u5982 NumPy\u3001Pandas\u3001Scikit-learn\u3001TensorFlow \u548c PyTorch\u3002\u6b64\u5916\uff0c\u8981\u6210\u4e3a\u4e00\u540d\u5408\u683c\u7684\u673a\u5668\u5b66\u4e60\u5de5\u7a0b\u5e08\uff0c\u8fd8\u9700\u8981\u6709\u575a\u5b9e\u7684\u6570\u636e\u5904\u7406\u4e0e\u5206\u6790\u80fd\u529b\uff0c\u5b83\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u7279\u5f81\u5de5\u7a0b\u7b49\u6280\u80fd\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u6570\u5b66\u548c\u7edf\u8ba1\u5b66\u57fa\u7840<\/h3>\n<\/p>\n<p><h4>\u6570\u5b66\u77e5\u8bc6<\/h4>\n<\/p>\n<p><p>\u673a\u5668\u5b66\u4e60\u5f3a\u4f9d\u8d56\u4e8e\u6570\u5b66\u6a21\u578b\uff0c\u56e0\u6b64\u5bf9\u4e8e\u96f6\u57fa\u7840\u5b66\u4e60\u8005\u6765\u8bf4\uff0c\u4e86\u89e3\u548c\u638c\u63e1\u57fa\u672c\u7684\u6570\u5b66\u77e5\u8bc6\u662f\u9996\u8981\u4efb\u52a1\u3002<strong>\u7ebf\u6027\u4ee3\u6570<\/strong> \u4e3a\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u63d0\u4f9b\u4e86\u57fa\u7840\uff0c\u5305\u62ec\u77e9\u9635\u8fd0\u7b97\u3001\u5411\u91cf\u7a7a\u95f4\u548c\u7279\u5f81\u5206\u89e3\u7b49\uff1b<strong>\u6982\u7387\u8bba\u4e0e\u6570\u7406\u7edf\u8ba1<\/strong> 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\u7f16\u7a0b<\/h4>\n<\/p>\n<p><p>\u673a\u5668\u5b66\u4e60\u754c\u4e3b\u6d41\u7684\u7f16\u7a0b\u8bed\u8a00\u662f Python\uff0c\u7531\u4e8e\u5176\u7b80\u6d01\u7684\u8bed\u6cd5\u548c\u5f3a\u5927\u7684\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u4f7f\u5176\u6210\u4e3a\u5b66\u4e60\u673a\u5668\u5b66\u4e60\u7684\u9996\u9009\u8bed\u8a00\u3002<strong>\u5b66\u4e60\u57fa\u7840\u7684 Python \u7f16\u7a0b<\/strong> \u5305\u62ec\u53d8\u91cf\u3001\u63a7\u5236\u7ed3\u6784\u3001\u51fd\u6570\u3001\u7c7b\u548c\u6a21\u5757\u7b49\u5185\u5bb9\u3002\u8fdb\u9636\u5b66\u4e60\uff0c\u9700\u8981\u638c\u63e1 Python \u7684\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5904\u7406\u65b9\u9762\u7684\u5e93\uff0c\u5982 NumPy \u7528\u4e8e\u9ad8\u6548\u7684\u6570\u503c\u8ba1\u7b97\u3001Pandas \u7528\u4e8e\u6570\u636e\u64cd\u4f5c\u3001Matplotlib \u548c Seaborn \u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u7b49\u3002<\/p>\n<\/p>\n<p><h4>\u5176\u4ed6\u7f16\u7a0b\u8bed\u80fd\u529b<\/h4>\n<\/p>\n<p><p>\u867d\u7136 Python \u662f\u9996\u9009\uff0c\u4f46\u5176\u4ed6\u7f16\u7a0b\u8bed\u8a00\u5982 R\u3001Java \u6216 C++ \u4e5f\u5728\u67d0\u4e9b\u9886\u57df\u5e7f\u6cdb\u4f7f\u7528\u3002\u5b66\u4e60\u673a\u5668\u5b66\u4e60\u4e0d\u5fc5\u5168\u90e8\u638c\u63e1\u8fd9\u4e9b\u8bed\u8a00\uff0c\u4f46\u81f3\u5c11\u5e94\u5bf9\u5176\u4e2d\u4e00\u79cd\u6216\u4e24\u79cd\u6709\u6240\u4e86\u89e3\uff0c\u8fd9\u6837\u53ef\u4ee5\u5728\u5fc5\u8981\u65f6\u66f4\u7075\u6d3b\u5730\u9002\u5e94\u4e0d\u540c\u7684\u5de5\u4f5c\u73af\u5883\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u6570\u636e\u5904\u7406\u4e0e\u5206\u6790\u80fd\u529b<\/h3>\n<\/p>\n<p><h4>\u6570\u636e\u9884\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u9884\u5904\u7406\u662f\u673a\u5668\u5b66\u4e60\u6d41\u7a0b\u4e2d\u91cd\u8981\u7684\u4e00\u73af\uff0c\u56e0\u4e3a\u6a21\u578b\u7684\u6027\u80fd\u5728\u5f88\u5927\u7a0b\u5ea6\u4e0a\u4f9d\u8d56\u4e8e\u6570\u636e\u8d28\u91cf\u3002<strong>\u6570\u636e\u6e05\u6d17\u3001\u5904\u7406\u7f3a\u5931\u503c\u3001\u5f02\u5e38\u503c\u5904\u7406\u3001\u6570\u636e\u6807\u51c6\u5316\u548c\u5f52\u4e00\u5316<\/strong> \u7b49\u90fd\u662f\u5fc5\u987b\u638c\u63e1\u7684\u6280\u80fd\u3002<\/p>\n<\/p>\n<p><h4>\u7279\u5f81\u5de5\u7a0b<\/h4>\n<\/p>\n<p><p>\u7279\u5f81\u5de5\u7a0b\u662f\u673a\u5668\u5b66\u4e60\u7684\u6838\u5fc3\u4e4b\u4e00\uff0c\u8d1f\u8d23\u5c06\u539f\u59cb\u6570\u636e\u8f6c\u6362\u4e3a\u80fd\u591f\u88ab\u6a21\u578b\u66f4\u597d\u5730\u5229\u7528\u7684\u5f62\u5f0f\u3002<strong>\u7279\u5f81\u9009\u62e9\u548c\u7279\u5f81\u63d0\u53d6<\/strong> \u5305\u62ec\u4e86\u5982\u4f55\u8bc6\u522b\u548c\u9009\u62e9\u5bf9\u9884\u6d4b\u6a21\u578b\u6709\u5e2e\u52a9\u7684\u7279\u5f81\uff0c<strong>\u964d\u7ef4\u6280\u672f<\/strong> \u5982\u4e3b\u6210\u5206\u5206\u6790\uff08PCA\uff09\u80fd\u591f\u5e2e\u52a9\u7b80\u5316\u6a21\u578b\uff0c\u63d0\u9ad8\u6548\u7387\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u673a\u5668\u5b66\u4e60\u7406\u8bba\u4e0e\u7b97\u6cd5<\/h3>\n<\/p>\n<p><h4>\u7406\u8bba\u77e5\u8bc6<\/h4>\n<\/p>\n<p><p>\u7406\u8bba\u77e5\u8bc6\u6784\u6210\u4e86\u5bf9\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u7406\u89e3\u7684\u57fa\u77f3\u3002<strong>\u76d1\u7763\u5b66\u4e60\u3001\u975e\u76d1\u7763\u5b66\u4e60\u3001\u534a\u76d1\u7763\u5b66\u4e60\u548c\u5f3a\u5316\u5b66\u4e60<\/strong> \u662f\u673a\u5668\u5b66\u4e60\u7684\u4e3b\u8981\u7c7b\u522b\uff0c\u4e86\u89e3\u8fd9\u4e9b\u5b66\u4e60\u7c7b\u578b\u7684\u57fa\u672c\u539f\u7406\u548c\u5e94\u7528\u573a\u666f\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002<\/p>\n<\/p>\n<p><h4>\u7b97\u6cd5\u5b9e\u64cd<\/h4>\n<\/p>\n<p><p><strong>\u56de\u5f52\u5206\u6790\u3001\u51b3\u7b56\u6811\u3001\u652f\u6301\u5411\u91cf\u673a\uff08SVM\uff09\u3001\u795e\u7ecf\u7f51\u7edc\u548c\u6df1\u5ea6\u5b66\u4e60\u3001\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5<\/strong> \u5982\u968f\u673a\u68ee\u6797\u548c\u68af\u5ea6\u63d0\u5347\u7b97\u6cd5\u7b49\u90fd\u662f\u673a\u5668\u5b66\u4e60\u4e2d\u5e38\u7528\u7684\u7b97\u6cd5\u3002\u5b66\u4e60\u5b83\u4eec\u7684\u7406\u8bba\u80cc\u666f\u3001\u5e94\u7528\u573a\u666f\u548c\u5728 Python \u4e2d\u7684\u5b9e\u73b0\u65b9\u6cd5\u662f\u8e0f\u5165\u673a\u5668\u5b66\u4e60\u5b9e\u8df5\u7684\u5173\u952e\u6b65\u9aa4\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u5b9e\u8df5\u5e94\u7528\u4e0e\u9879\u76ee\u7ecf\u9a8c<\/h3>\n<\/p>\n<p><h4>\u5b9e\u8df5\u9879\u76ee<\/h4>\n<\/p>\n<p><p>\u53ea\u6709\u901a\u8fc7\u5b9e\u8df5\uff0c\u624d\u80fd\u771f\u6b63\u638c\u63e1\u673a\u5668\u5b66\u4e60\u7684\u77e5\u8bc6\u3002\u5f00\u59cb\u65f6\u53ef\u4ee5\u4ece\u5c0f\u9879\u76ee\u505a\u8d77\uff0c\u5982\u4f7f\u7528\u7ecf\u5178\u7684\u673a\u5668\u5b66\u4e60\u6570\u636e\u96c6\u8fdb\u884c\u6570\u636e\u63a2\u7d22\u3001\u6a21\u578b\u6784\u5efa\u548c\u8bc4\u4ef7\u3002<strong>Kaggle \u7ade\u8d5b<\/strong> 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