{"id":324545,"date":"2024-05-21T21:04:51","date_gmt":"2024-05-21T13:04:51","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/324545.html"},"modified":"2024-05-21T21:04:59","modified_gmt":"2024-05-21T13:04:59","slug":"%e5%9c%a8%e5%a4%a7%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%e4%b8%ad%e5%93%aa%e4%ba%9b%e8%81%9a%e7%b1%bb%e7%ae%97%e6%b3%95%e6%98%af%e6%9c%80%e5%b8%b8%e4%bd%bf%e7%94%a8%e7%9a%84-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/324545.html","title":{"rendered":"\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\u54ea\u4e9b\u805a\u7c7b\u7b97\u6cd5\u662f\u6700\u5e38\u4f7f\u7528\u7684"},"content":{"rendered":"

\"\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\u54ea\u4e9b\u805a\u7c7b\u7b97\u6cd5\u662f\u6700\u5e38\u4f7f\u7528\u7684\"<\/p>\n

\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\uff0c\u6700\u5e38\u4f7f\u7528\u7684\u805a\u7c7b\u7b97\u6cd5\u5305\u62ecK-\u5747\u503c\uff08K-Means\uff09\u3001\u5c42\u6b21\u805a\u7c7b\uff08Hierarchical Clustering\uff09\u3001DBSCAN\uff08Density-Based Spatial Clustering of Applications with Noise\uff09\u3001\u8c31\u805a\u7c7b\uff08Spectral Clustering\uff09\u7b49\u3002\u8fd9\u4e9b\u7b97\u6cd5\u5404\u6709\u5176\u7279\u70b9\u548c\u5e94\u7528\u573a\u666f\uff0c\u4f46\u5728\u4f17\u591a\u7b97\u6cd5\u4e2d\uff0cK-\u5747\u503c\u7b97\u6cd5\u56e0\u5176\u7b80\u5355\u3001\u9ad8\u6548\u800c\u5e7f\u6cdb\u5e94\u7528\u4e8e\u5404\u4e2a\u9886\u57df<\/strong>\u3002K-\u5747\u503c\u7b97\u6cd5\u901a\u8fc7\u8fed\u4ee3\u5bfb\u627e\u805a\u7c7b\u4e2d\u5fc3\uff0c\u5c06\u6570\u636e\u70b9\u5206\u914d\u5230\u6700\u8fd1\u7684\u805a\u7c7b\u4e2d\u5fc3\uff0c\u76f4\u5230\u6ee1\u8db3\u505c\u6b62\u6761\u4ef6\uff0c\u5982\u805a\u7c7b\u4e2d\u5fc3\u4e0d\u518d\u53d8\u5316\u6216\u8fbe\u5230\u8bbe\u5b9a\u7684\u8fed\u4ee3\u6b21\u6570\u3002\u8fd9\u79cd\u7b97\u6cd5\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\uff0c\u56e0\u4e3a\u5b83\u7684\u8ba1\u7b97\u590d\u6742\u5ea6\u76f8\u5bf9\u8f83\u4f4e\uff0c\u4e14\u5bb9\u6613\u7406\u89e3\u548c\u5b9e\u73b0\u3002\u7136\u800c\uff0cK-\u5747\u503c\u7b97\u6cd5\u4e5f\u6709\u5176\u5c40\u9650\u6027\uff0c\u5982\u9700\u9884\u5148\u6307\u5b9a\u805a\u7c7b\u6570\u76eeK\u503c\uff0c\u4e14\u5bf9\u566a\u58f0\u548c\u5f02\u5e38\u503c\u6bd4\u8f83\u654f\u611f\u3002<\/p>\n<\/p>\n

\u4e00\u3001K-\u5747\u503c\uff08K-MEANS\uff09\u805a\u7c7b\u7b97\u6cd5<\/h3>\n<\/p>\n

K-\u5747\u503c\u7b97\u6cd5\u662f\u6700\u6d41\u884c\u7684\u805a\u7c7b\u7b97\u6cd5\u4e4b\u4e00\uff0c\u5b83\u901a\u8fc7\u8fed\u4ee3\u6765\u4f18\u5316\u805a\u7c7b\u4e2d\u5fc3\uff0c\u4f7f\u5f97\u6bcf\u4e2a\u6570\u636e\u70b9\u5230\u5176\u805a\u7c7b\u4e2d\u5fc3\u7684\u8ddd\u79bb\u4e4b\u548c\u6700\u5c0f\u3002\u7b97\u6cd5\u5f00\u59cb\u65f6\u968f\u673a\u9009\u62e9K\u4e2a\u70b9\u4f5c\u4e3a\u521d\u59cb\u805a\u7c7b\u4e2d\u5fc3\uff0c\u7136\u540e\u6309\u7167\u6570\u636e\u70b9\u5230\u8fd9\u4e9b\u4e2d\u5fc3\u7684\u8ddd\u79bb\u5c06\u6570\u636e\u70b9\u5206\u914d\u5230\u6700\u8fd1\u7684\u805a\u7c7b\u4e2d\u3002\u4e4b\u540e\uff0c\u91cd\u65b0\u8ba1\u7b97\u6bcf\u4e2a\u805a\u7c7b\u7684\u4e2d\u5fc3\u70b9\uff0c\u5e76\u91cd\u590d\u4e0a\u8ff0\u8fc7\u7a0b\u76f4\u5230\u6ee1\u8db3\u505c\u6b62\u6761\u4ef6\u3002<\/p>\n<\/p>\n

K-\u5747\u503c\u7b97\u6cd5\u7684\u4e3b\u8981\u4f18\u70b9\u662f\u7b80\u5355\u6613\u61c2\u3001\u8ba1\u7b97\u6548\u7387\u9ad8<\/strong>\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\u3002\u7136\u800c\uff0c\u5b83\u4e5f\u6709\u4e00\u4e9b\u7f3a\u70b9\uff0c\u6bd4\u5982\u9700\u8981\u9884\u5148\u786e\u5b9a\u805a\u7c7b\u6570\u76eeK\uff0c\u5bf9\u521d\u59cb\u805a\u7c7b\u4e2d\u5fc3\u7684\u9009\u62e9\u654f\u611f\uff0c\u53ef\u80fd\u5bfc\u81f4\u5c40\u90e8\u6700\u4f18\u89e3\uff0c\u800c\u4e14\u5bf9\u566a\u58f0\u548c\u5f02\u5e38\u503c\u6bd4\u8f83\u654f\u611f\u3002<\/p>\n<\/p>\n

\u4e8c\u3001\u5c42\u6b21\u805a\u7c7b\uff08HIERARCHICAL CLUSTERING\uff09<\/h3>\n<\/p>\n

\u5c42\u6b21\u805a\u7c7b\u662f\u53e6\u4e00\u79cd\u5e38\u7528\u7684\u805a\u7c7b\u65b9\u6cd5\uff0c\u5b83\u901a\u8fc7\u6784\u5efa\u805a\u7c7b\u7684\u5c42\u6b21\u7ed3\u6784\u6765\u8fdb\u884c\u6570\u636e\u70b9\u7684\u5206\u7ec4\u3002\u5c42\u6b21\u805a\u7c7b\u7b97\u6cd5\u53ef\u4ee5\u5206\u4e3a\u4e24\u79cd\u7c7b\u578b\uff1a\u51dd\u805a\u7684\u5c42\u6b21\u805a\u7c7b\u548c\u5206\u88c2\u7684\u5c42\u6b21\u805a\u7c7b\u3002\u51dd\u805a\u7684\u5c42\u6b21\u805a\u7c7b\u4ece\u5c06\u6bcf\u4e2a\u6570\u636e\u70b9\u770b\u4f5c\u4e00\u4e2a\u5355\u72ec\u7684\u805a\u7c7b\u5f00\u59cb\uff0c\u7136\u540e\u9010\u6e10\u5408\u5e76\u8fd9\u4e9b\u805a\u7c7b\u76f4\u5230\u8fbe\u5230\u4e00\u4e2a\u5927\u7684\u805a\u7c7b\u6216\u6ee1\u8db3\u7279\u5b9a\u7684\u505c\u6b62\u6761\u4ef6\u3002\u5206\u88c2\u7684\u5c42\u6b21\u805a\u7c7b\u5219\u662f\u4ece\u4e00\u4e2a\u5305\u542b\u6240\u6709\u6570\u636e\u70b9\u7684\u5927\u805a\u7c7b\u5f00\u59cb\uff0c\u9010\u6b65\u5c06\u5176\u5206\u88c2\u6210\u66f4\u5c0f\u7684\u805a\u7c7b\u3002<\/p>\n<\/p>\n

\u5c42\u6b21\u805a\u7c7b\u7b97\u6cd5\u7684\u4e00\u4e2a\u91cd\u8981\u4f18\u70b9\u662f\u4e0d\u9700\u8981\u9884\u5148\u6307\u5b9a\u805a\u7c7b\u6570\u76ee\uff0c\u5b83\u53ef\u4ee5\u63d0\u4f9b\u4e00\u4e2a\u805a\u7c7b\u7684\u5c42\u6b21\u7ed3\u6784\uff0c\u4ece\u800c\u4f7f\u5f97\u5206\u6790\u4eba\u5458\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u8981\u9009\u62e9\u5408\u9002\u7684\u805a\u7c7b\u5c42\u6b21\u3002\u7136\u800c\uff0c\u5c42\u6b21\u805a\u7c7b\u7b97\u6cd5\u7684\u8ba1\u7b97\u590d\u6742\u5ea6\u76f8\u5bf9\u8f83\u9ad8\uff0c\u7279\u522b\u662f\u5bf9\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u8fd9\u53ef\u80fd\u6210\u4e3a\u4e00\u4e2a\u95ee\u9898\u3002<\/p>\n<\/p>\n

\u4e09\u3001DBSCAN\uff08DENSITY-BASED SPATIAL CLUSTERING OF APPLICATIONS WITH NOISE\uff09<\/h3>\n<\/p>\n

DBSCAN\u662f\u4e00\u79cd\u57fa\u4e8e\u5bc6\u5ea6\u7684\u7a7a\u95f4\u805a\u7c7b\u7b97\u6cd5\uff0c\u5b83\u80fd\u591f\u5728\u5e26\u6709\u566a\u58f0\u7684\u6570\u636e\u96c6\u4e2d\u53d1\u73b0\u4efb\u610f\u5f62\u72b6\u7684\u7c07\u3002DBSCAN\u7b97\u6cd5\u7684\u6838\u5fc3\u6982\u5ff5\u662f\u6838\u5fc3\u70b9\u3001\u8fb9\u754c\u70b9\u548c\u566a\u58f0\u70b9\u3002\u7b97\u6cd5\u9996\u5148\u786e\u5b9a\u6838\u5fc3\u70b9\uff0c\u7136\u540e\u901a\u8fc7\u6838\u5fc3\u70b9\u76f8\u4e92\u8fde\u63a5\u5f62\u6210\u7c07\uff0c\u6700\u540e\u8bc6\u522b\u51fa\u8fb9\u754c\u70b9\u548c\u566a\u58f0\u70b9\u3002<\/p>\n<\/p>\n

DBSCAN\u7b97\u6cd5\u7684\u4e00\u4e2a\u663e\u8457\u4f18\u70b9\u662f\u4e0d\u9700\u8981\u9884\u5148\u6307\u5b9a\u805a\u7c7b\u6570\u91cf<\/strong>\uff0c\u5e76\u4e14\u5bf9\u6570\u636e\u96c6\u4e2d\u7684\u566a\u58f0\u548c\u5f02\u5e38\u503c\u5177\u6709\u826f\u597d\u7684\u9c81\u68d2\u6027\u3002\u4f46\u662f\uff0cDBSCAN\u5bf9\u5176\u53c2\u6570\uff08\u90bb\u57df\u5927\u5c0f\u548c\u6700\u5c0f\u70b9\u6570\uff09\u7684\u9009\u62e9\u76f8\u5f53\u654f\u611f\uff0c\u4e0d\u5f53\u7684\u53c2\u6570\u8bbe\u7f6e\u53ef\u80fd\u5bfc\u81f4\u805a\u7c7b\u7ed3\u679c\u7684\u8d28\u91cf\u5927\u5e45\u4e0b\u964d\u3002<\/p>\n<\/p>\n

\u56db\u3001\u8c31\u805a\u7c7b\uff08SPECTRAL CLUSTERING\uff09<\/h3>\n<\/p>\n

\u8c31\u805a\u7c7b\u7b97\u6cd5\u662f\u57fa\u4e8e\u56fe\u8bba\u7684\u4e00\u79cd\u805a\u7c7b\u65b9\u6cd5\uff0c\u5b83\u5c06\u805a\u7c7b\u95ee\u9898\u8f6c\u5316\u4e3a\u56fe\u7684\u5207\u5206\u95ee\u9898\u3002\u7b97\u6cd5\u9996\u5148\u6784\u5efa\u4e00\u4e2a\u4ee3\u8868\u6570\u636e\u70b9\u76f8\u4f3c\u5ea6\u7684\u56fe\uff0c\u7136\u540e\u901a\u8fc7\u5206\u6790\u56fe\u7684\u8c31\uff08\u5373\u56fe\u7684\u62c9\u666e\u62c9\u65af\u77e9\u9635\u7684\u7279\u5f81\u5411\u91cf\uff09\u6765\u8fdb\u884c\u805a\u7c7b\u3002<\/p>\n<\/p>\n

\u8c31\u805a\u7c7b\u7b97\u6cd5\u7684\u4e00\u4e2a\u4e3b\u8981\u4f18\u70b9\u662f\u80fd\u591f\u8bc6\u522b\u51fa\u4efb\u610f\u5f62\u72b6\u7684\u7c07\uff0c\u4e14\u5bf9\u6570\u636e\u7684\u7f29\u653e\u4e0d\u654f\u611f\u3002\u7136\u800c\uff0c\u8c31\u805a\u7c7b\u7684\u8ba1\u7b97\u6210\u672c\u76f8\u5bf9\u8f83\u9ad8\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\u65f6\u3002\u6b64\u5916\uff0c\u50cfK-\u5747\u503c\u7b97\u6cd5\u4e00\u6837\uff0c\u8c31\u805a\u7c7b\u4e5f\u9700\u8981\u9884\u5148\u6307\u5b9a\u805a\u7c7b\u7684\u6570\u91cf\u3002<\/p>\n<\/p>\n

\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u9009\u62e9\u5408\u9002\u7684\u805a\u7c7b\u7b97\u6cd5\u9700\u8981\u8003\u8651\u6570\u636e\u7684\u7279\u6027\u3001\u7b97\u6cd5\u7684\u4f18\u7f3a\u70b9\u4ee5\u53ca\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u3002\u4e0d\u540c\u7684\u7b97\u6cd5\u53ef\u80fd\u5728\u4e0d\u540c\u7684\u6570\u636e\u96c6\u4e0a\u8868\u73b0\u51fa\u4e0d\u540c\u7684\u805a\u7c7b\u6548\u679c\uff0c\u56e0\u6b64\u5728\u5b9e\u9645\u64cd\u4f5c\u4e2d\u53ef\u80fd\u9700\u8981\u5c1d\u8bd5\u591a\u79cd\u7b97\u6cd5\uff0c\u4ee5\u627e\u5230\u6700\u9002\u5408\u7279\u5b9a\u9700\u6c42\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<\/p>\n

\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n

1. \u54ea\u4e9b\u805a\u7c7b\u7b97\u6cd5\u5e38\u7528\u4e8e\u5927\u6570\u636e\u5206\u6790\uff1f<\/strong><\/p>\n

\u5927\u6570\u636e\u5206\u6790\u4e2d\u5e38\u7528\u7684\u805a\u7c7b\u7b97\u6cd5\u5305\u62ecK\u5747\u503c\u805a\u7c7b\u3001DBSCAN\u5bc6\u5ea6\u805a\u7c7b\u548c\u5c42\u6b21\u805a\u7c7b\u7b49\u3002\u8fd9\u4e9b\u7b97\u6cd5\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\u88ab\u5e7f\u6cdb\u4f7f\u7528\uff0c\u56e0\u4e3a\u5b83\u4eec\u5177\u6709\u7b80\u5355\u6613\u61c2\u3001\u53ef\u6269\u5c55\u6027\u5f3a\u548c\u9002\u7528\u4e8e\u4e0d\u540c\u7c7b\u578b\u6570\u636e\u7b49\u4f18\u52bf\u3002<\/p>\n

2. K\u5747\u503c\u805a\u7c7b\u7b97\u6cd5\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e94\u7528\u573a\u666f\u6709\u54ea\u4e9b\uff1f<\/strong><\/p>\n

K\u5747\u503c\u805a\u7c7b\u7b97\u6cd5\u5e38\u7528\u4e8e\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u6570\u636e\u5206\u7c7b\u548c\u805a\u7c7b\u4efb\u52a1\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5229\u7528K\u5747\u503c\u805a\u7c7b\u7b97\u6cd5\u5c06\u7528\u6237\u6570\u636e\u5206\u6210\u4e0d\u540c\u7684\u7fa4\u7ec4\uff0c\u7136\u540e\u9488\u5bf9\u6bcf\u4e2a\u7fa4\u7ec4\u8fdb\u884c\u4e2a\u6027\u5316\u63a8\u8350\u3002\u6b64\u5916\uff0cK\u5747\u503c\u805a\u7c7b\u7b97\u6cd5\u8fd8\u53ef\u4ee5\u7528\u4e8e\u56fe\u50cf\u5206\u5272\u3001\u5f02\u5e38\u68c0\u6d4b\u548c\u6a21\u5f0f\u8bc6\u522b\u7b49\u9886\u57df\u3002<\/p>\n

3. DBSCAN\u5bc6\u5ea6\u805a\u7c7b\u7b97\u6cd5\u5728\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u4f18\u52bf\u662f\u4ec0\u4e48\uff1f<\/strong><\/p>\n

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