{"id":262052,"date":"2024-05-15T14:22:00","date_gmt":"2024-05-15T06:22:00","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/262052.html"},"modified":"2024-05-15T14:22:06","modified_gmt":"2024-05-15T06:22:06","slug":"%e8%81%9a%e7%b1%bb%e6%95%85%e9%9a%9c%e8%af%8a%e6%96%ad%e5%ba%94%e8%af%a5%e6%80%8e%e4%b9%88%e6%90%9e%ef%bc%8c%e6%9c%89%e6%b2%a1%e6%9c%89%e4%bb%80%e4%b9%88%e4%bb%a3%e7%a0%81%e8%83%bd%e8%bf%9b%e8%a1%8c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/262052.html","title":{"rendered":"\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u5e94\u8be5\u600e\u4e48\u641e\uff0c\u6709\u6ca1\u6709\u4ec0\u4e48\u4ee3\u7801\u80fd\u8fdb\u884c\u5b66\u4e60\u7684"},"content":{"rendered":"

\"\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u5e94\u8be5\u600e\u4e48\u641e\uff0c\u6709\u6ca1\u6709\u4ec0\u4e48\u4ee3\u7801\u80fd\u8fdb\u884c\u5b66\u4e60\u7684\"<\/p>\n

\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u4e3b\u8981\u901a\u8fc7\u5c06\u6570\u636e\u96c6\u4e2d\u76f8\u4f3c\u6570\u636e\u805a\u96c6\u6210\u7ec4\u8fdb\u884c\u5de5\u4e1a\u7cfb\u7edf\u7684\u6545\u969c\u5206\u6790\u548c\u68c0\u6d4b\u3002\u9996\u5148\u3001\u9700\u660e\u786e\u6545\u969c\u7279\u5f81\u5e76\u9009\u62e9\u5408\u9002\u7684\u805a\u7c7b\u7b97\u6cd5\uff1b\u5176\u6b21\u3001\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u4ee5\u51c6\u5907\u9002\u5408\u805a\u7c7b\u7684\u6570\u636e\u96c6\uff1b\u63a5\u7740\u3001\u5229\u7528\u9009\u62e9\u7684\u805a\u7c7b\u7b97\u6cd5\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff1b\u6700\u540e\u3001\u5206\u6790\u805a\u7c7b\u7ed3\u679c\u5e76\u5c06\u5176\u5e94\u7528\u4e8e\u6545\u969c\u8bca\u65ad\u3002<\/strong> <\/p>\n<\/p>\n

\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0cK-Means\u7b97\u6cd5\u56e0\u5176\u7b80\u5355\u9ad8\u6548\u800c\u5e7f\u6cdb\u5e94\u7528\u4e8e\u6545\u969c\u8bca\u65ad\u573a\u666f\u3002\u8be5\u7b97\u6cd5\u901a\u8fc7\u8fed\u4ee3\u7684\u65b9\u5f0f\u5c06\u6570\u636e\u5206\u4e3aK\u4e2a\u96c6\u7fa4\uff0c\u4ee5\u4f7f\u6bcf\u4e2a\u6570\u636e\u70b9\u4e0e\u5176\u6240\u5c5e\u7684\u96c6\u7fa4\u4e2d\u5fc3\uff08\u8d28\u5fc3\uff09\u7684\u8ddd\u79bb\u6700\u5c0f\u5316\u3002\u65e8\u5728\u4ece\u6570\u636e\u96c6\u7684\u5185\u5728\u7ed3\u6784\u4e2d\u63d0\u53d6\u6709\u52a9\u4e8e\u6545\u969c\u8bc6\u522b\u7684\u6a21\u5f0f\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u6545\u969c\u7279\u5f81\u9009\u62e9<\/h3>\n<\/p>\n

\u5728\u8fdb\u884c\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u8fdb\u884c\u6545\u969c\u7279\u5f81\u9009\u62e9\u3002\u8fd9\u4e9b\u7279\u5f81\u5e94\u5f53\u80fd\u591f\u53cd\u6620\u51fa\u7cfb\u7edf\u72b6\u6001\u7684\u91cd\u8981\u4fe1\u606f\uff0c\u5e76\u80fd\u591f\u533a\u5206\u6b63\u5e38\u72b6\u6001\u4e0e\u6545\u969c\u72b6\u6001\u3002<\/p>\n<\/p>\n

\u9009\u53d6\u4f20\u611f\u5668\u8bfb\u6570\u3001\u5386\u53f2\u7ef4\u62a4\u8bb0\u5f55\u6216\u7cfb\u7edf\u65e5\u5fd7\u4e2d\u7684\u5173\u952e\u6307\u6807<\/strong>\uff0c\u5982\u6e29\u5ea6\u3001\u632f\u52a8\u3001\u7535\u6d41\u3001\u538b\u529b\u7b49\uff0c\u4f5c\u4e3a\u6545\u969c\u7279\u5f81\u3002\u5bf9\u4e8e\u9ad8\u7ef4\u6570\u636e\uff0c\u53ef\u4ee5\u91c7\u7528\u964d\u7ef4\u6280\u672f\uff0c\u5982\u4e3b\u6210\u5206\u5206\u6790(PCA)\u6216\u7ebf\u6027\u5224\u522b\u5206\u6790(LDA)\uff0c\u4ee5\u63d0\u53d6\u6700\u80fd\u4ee3\u8868\u6570\u636e\u7279\u6027\u7684\u4e3b\u8981\u6210\u5206\u3002<\/p>\n<\/p>\n

\u4e00\u79cd\u5e38\u89c1\u7684\u7279\u5f81\u9009\u62e9\u6280\u672f\u662f\u5229\u7528\u76f8\u5173\u7cfb\u6570\u6216\u4e92\u4fe1\u606f\u5bf9\u7279\u5f81\u8fdb\u884c\u8bc4\u5206\uff0c\u9ad8\u5206\u7684\u7279\u5f81\u88ab\u8ba4\u4e3a\u662f\u5bf9\u9884\u6d4b\u6545\u969c\u72b6\u6001\u66f4\u6709\u5e2e\u52a9\u7684\u7279\u5f81\u3002<\/p>\n<\/p>\n

\u4e8c\u3001\u6570\u636e\u9884\u5904\u7406<\/h3>\n<\/p>\n

\u6570\u636e\u9884\u5904\u7406\u662f\u805a\u7c7b\u5206\u6790\u7684\u57fa\u7840\uff0c\u5176\u76ee\u7684\u662f\u4f7f\u539f\u59cb\u6570\u636e\u9002\u5e94\u6240\u9009\u805a\u7c7b\u7b97\u6cd5\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n

\u6570\u636e\u6807\u51c6\u5316<\/strong>\u662f\u6700\u5173\u952e\u7684\u9884\u5904\u7406\u6b65\u9aa4\u4e4b\u4e00\uff0c\u5c06\u6570\u636e\u7684\u5747\u503c\u4e2d\u5fc3\u5316\u4e3a0\uff0c\u6807\u51c0\u5dee\u89c4\u4e00\u5316\u4e3a1\u3002\u5f53\u7279\u5f81\u91cf\u7eb2\u4e0d\u540c\u65f6\uff0c\u6807\u51c6\u5316\u8fc7\u7a0b\u80fd\u591f\u786e\u4fdd\u6bcf\u4e2a\u7279\u5f81\u5bf9\u805a\u7c7b\u7ed3\u679c\u7684\u8d21\u732e\u76f8\u7b49\u3002<\/p>\n<\/p>\n

\u6570\u636e\u6e05\u6d17\u540c\u6837\u91cd\u8981\uff0c\u5b83\u6d89\u53ca\u5230\u68c0\u6d4b\u548c\u4fee\u6b63\u6570\u636e\u96c6\u4e2d\u7684\u9519\u8bef\u6216\u4e0d\u4e00\u81f4\uff0c\u5305\u62ec\u586b\u5145\u7f3a\u5931\u503c\u3001\u5e73\u6ed1\u566a\u58f0\u6570\u636e\u70b9\uff0c\u4ee5\u53ca\u8bc6\u522b\u5e76\u53bb\u9664\u79bb\u7fa4\u70b9\u3002<\/p>\n<\/p>\n

\u4e09\u3001\u9009\u62e9\u5408\u9002\u7684\u805a\u7c7b\u7b97\u6cd5<\/h3>\n<\/p>\n

\u6839\u636e\u6545\u969c\u8bca\u65ad\u7684\u9700\u6c42\uff0c\u9009\u62e9\u5408\u9002\u7684\u805a\u7c7b\u7b97\u6cd5\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002K-Means\u7b97\u6cd5\u5e7f\u4e3a\u4eba\u77e5\u4e14\u6613\u4e8e\u5b9e\u73b0\uff0c\u4f46\u9700\u8981\u9884\u5148\u5b9a\u4e49\u805a\u7c7b\u6570\u76ee<\/strong>\u3002<\/p>\n<\/p>\n

\u5176\u4ed6\u5982\u57fa\u4e8e\u5bc6\u5ea6\u7684DBSCAN\u7b97\u6cd5\u53ef\u4ee5\u8bc6\u522b\u4efb\u610f\u5f62\u72b6\u7684\u7c07\uff0c\u5e76\u80fd\u8fc7\u6ee4\u6389\u566a\u58f0\u70b9\u3002\u5c42\u6b21\u805a\u7c7b\u7b97\u6cd5\u5219\u901a\u8fc7\u6784\u5efa\u5d4c\u5957\u7684\u7c07\u6811\u72b6\u56fe\uff0c\u9002\u7528\u4e8e\u90a3\u4e9b\u9700\u8981\u5c42\u6b21\u5206\u89e3\u6545\u969c\u6a21\u5f0f\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n

\u6bcf\u79cd\u7b97\u6cd5\u90fd\u6709\u5176\u5e94\u7528\u573a\u666f\u548c\u5c40\u9650\u6027\uff0c\u56e0\u6b64\uff0c\u5728\u6545\u969c\u8bca\u65ad\u4e2d\u9009\u62e9\u5408\u9002\u7684\u7b97\u6cd5\u9700\u8981\u8003\u8651\u6570\u636e\u7684\u7279\u6027\u548c\u6545\u969c\u8bca\u65ad\u7684\u5177\u4f53\u9700\u6c42\u3002<\/p>\n<\/p>\n

\u56db\u3001\u805a\u7c7b\u7ec6\u8282\u4e0e\u5b9e\u73b0<\/h3>\n<\/p>\n

\u5728\u786e\u5b9a\u4e86\u805a\u7c7b\u7b97\u6cd5\u540e\uff0c\u5c31\u53ef\u4ee5\u8fdb\u884c\u7b97\u6cd5\u5b9e\u73b0\u548c\u8c03\u6574\u7b97\u6cd5\u53c2\u6570\u6765\u4f18\u5316\u805a\u7c7b\u6548\u679c\u4e86\u3002<\/p>\n<\/p>\n

\u4ee5K-Means\u7b97\u6cd5\u4e3a\u4f8b\uff0c\u5173\u952e\u7684\u6b65\u9aa4\u5305\u62ec\u521d\u59cb\u5316K\u4e2a\u8d28\u5fc3\u3001\u5206\u914d\u6570\u636e\u70b9\u5230\u6700\u8fd1\u7684\u8d28\u70b9\u3001\u66f4\u65b0\u8d28\u70b9\u4f4d\u7f6e\uff0c\u8fd9\u4e2a\u8fc7\u7a0b\u91cd\u590d\u8fed\u4ee3\u76f4\u5230\u6ee1\u8db3\u505c\u6b62\u6761\u4ef6\uff0c\u901a\u5e38\u662f\u8d28\u5fc3\u7684\u4f4d\u7f6e\u53d8\u5316\u5c0f\u4e8e\u67d0\u4e2a\u9608\u503c\u6216\u8fbe\u5230\u9884\u5b9a\u7684\u8fed\u4ee3\u6b21\u6570\u3002<\/p>\n<\/p>\n

\u5bf9\u4e8e\u6545\u969c\u8bca\u65ad\u5e94\u7528\uff0c\u8bc4\u4f30\u805a\u7c7b\u6548\u679c\u7684\u6307\u6807\u5305\u62ec\u7d27\u5bc6\u5ea6\u548c\u5206\u79bb\u5ea6<\/strong>\u3002\u7d27\u5bc6\u5ea6\u6d4b\u91cf\u7684\u662f\u540c\u4e00\u4e2a\u7c07\u5185\u6837\u672c\u7684\u76f8\u4f3c\u5ea6\uff0c\u800c\u5206\u79bb\u5ea6\u5219\u662f\u4e0d\u540c\u7c07\u95f4\u6837\u672c\u7684\u5dee\u5f02\u5ea6\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u4e00\u4e2a\u7c07\u5185\u7684\u6570\u636e\u70b9\u5e94\u8be5\u662f\u9ad8\u5ea6\u76f8\u4f3c\u7684\uff0c\u800c\u4e0d\u540c\u7684\u7c07\u4e4b\u95f4\u5e94\u8be5\u533a\u5206\u5f00\u660e\u663e\u3002<\/p>\n<\/p>\n

\u4e94\u3001\u805a\u7c7b\u7ed3\u679c\u5206\u6790\u4e0e\u6545\u969c\u8bca\u65ad<\/h3>\n<\/p>\n

\u805a\u7c7b\u540e\u7684\u6570\u636e\u5206\u6790\u662f\u5173\u952e\u6b65\u9aa4<\/strong>\uff0c\u9700\u8981\u5c06\u805a\u7c7b\u7ed3\u679c\u4e0e\u5b9e\u9645\u7684\u6545\u969c\u77e5\u8bc6\u7ed3\u5408\u8d77\u6765\u3002\u901a\u8fc7\u6bd4\u8f83\u4e0d\u540c\u7c07\u4e2d\u7684\u6570\u636e\u6a21\u5f0f\uff0c\u53ef\u4ee5\u8bc6\u522b\u51fa\u6f5c\u5728\u7684\u6545\u969c\u7279\u5f81\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4e00\u4e2a\u7c07\u5305\u542b\u7684\u6570\u636e\u70b9\u5728\u67d0\u7279\u5f81\u7ef4\u5ea6\u4e0a\u8868\u73b0\u5f02\u5e38\uff0c\u53ef\u80fd\u5c31\u6307\u793a\u4e86\u8be5\u7279\u5f81\u7ef4\u5ea6\u76f8\u5173\u7684\u6545\u969c\u3002<\/p>\n<\/p>\n

\u5168\u9762\u7684\u805a\u7c7b\u7ed3\u679c\u5206\u6790\u4f9d\u8d56\u4e8e\u4e13\u5bb6\u7684\u77e5\u8bc6\u548c\u7ecf\u9a8c\uff0c\u4ee5\u786e\u4fdd\u80fd\u6b63\u786e\u5730\u89e3\u91ca\u805a\u7c7b\u5f62\u6210\u7684\u7c07\u548c\u8fd9\u4e9b\u7c07\u4e0e\u5177\u4f53\u6545\u969c\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/p>\n<\/p>\n

\u516d\u3001\u4ee3\u7801\u5b9e\u4f8b\u548c\u5b66\u4e60\u8d44\u6e90<\/h3>\n<\/p>\n

\u6700\u540e\uff0c\u5b9e\u8df5\u662f\u6700\u597d\u7684\u5b66\u4e60\u65b9\u5f0f\u3002Python\u4e2d\u5e38\u7528\u7684\u673a\u5668\u5b66\u4e60<\/a>\u5e93\u5982scikit-learn\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u805a\u7c7b\u7b97\u6cd5\u5b9e\u73b0\uff0c\u5305\u62ecK-Means\u3001DBSCAN\u548c\u5c42\u6b21\u805a\u7c7b\u7b97\u6cd5\u7b49\uff0c\u5e76\u4e14\u6709\u5927\u91cf\u7684\u5728\u7ebf\u8d44\u6e90\u548c\u793e\u533a\u652f\u6301\u6559\u7a0b\u63d0\u4f9b\u5b66\u4e60\u548c\u5b9e\u8df5\u7684\u673a\u4f1a\u3002<\/p>\n<\/p>\n

from sklearn.cluster import KMeans<\/p>\n
from sklearn.preprocessing import StandardScaler<\/p>\n
import numpy as np<\/p>\n
\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
data = np.array([<\/p>\n
  \/\/ \u6570\u636e\u96c6\u7684\u7279\u5f81\u503c<\/p>\n
])<\/p>\n
\u6570\u636e\u6807\u51c6\u5316<\/strong><\/h2>\n
scaler = StandardScaler()<\/p>\n
data_normalized = scaler.fit_transform(data)<\/p>\n
\u5e94\u7528K-Means\u805a\u7c7b<\/strong><\/h2>\n
kmeans = KMeans(n_clusters=3, random_state=0)<\/p>\n
clusters = kmeans.fit_predict(data_normalized)<\/p>\n
\u5206\u6790\u6545\u969c\u8bca\u65ad\u7ed3\u679c<\/strong><\/h2>\n
\/\/ \u6839\u636e\u805a\u7c7b\u7ed3\u679c\u8fdb\u884c\u540e\u7eed\u5206\u6790<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0a\u662f\u4e00\u4e2a\u7b80\u5355\u7684K-Means\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u4ee3\u7801\u6837\u4f8b\uff0c\u5728\u4f7f\u7528\u65f6\u9700\u8981\u6839\u636e\u5b9e\u9645\u6570\u636e\u96c6\u8fdb\u884c\u4fee\u6539\u548c\u8c03\u6574\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u516d\u4e2a\u6b65\u9aa4\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u5b9e\u73b0\u805a\u7c7b\u6545\u969c\u8bca\u65ad\uff0c\u5e76\u53ef\u4ee5\u901a\u8fc7\u5b9e\u8df5\u548c\u4ee3\u7801\u5b9e\u4f8b\u52a0\u6df1\u7406\u89e3\uff0c\u63d0\u5347\u6545\u969c\u8bca\u65ad\u7684\u80fd\u529b\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
1. \u805a\u7c7b\u6545\u969c\u8bca\u65ad\u662f\u4ec0\u4e48\uff1f\u6709\u54ea\u4e9b\u65b9\u6cd5\u548c\u5de5\u5177\u53ef\u4ee5\u7528\u4e8e\u8bca\u65ad\uff1f<\/strong><\/p>\n
\u805a\u7c7b\u6545\u969c\u8bca\u65ad\u662f\u4e00\u79cd\u901a\u8fc7\u9488\u5bf9\u4e00\u7ec4\u76f8\u5173\u7684\u6570\u636e\u70b9\u8fdb\u884c\u805a\u7c7b\u5206\u6790\u6765\u68c0\u6d4b\u548c\u8bca\u65ad\u6545\u969c\u7684\u65b9\u6cd5\u3002\u5b83\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u627e\u51fa\u5f02\u5e38\u6570\u636e\u70b9\u3001\u7fa4\u96c6\u7684\u504f\u79fb\u4ee5\u53ca\u5176\u4ed6\u4e0e\u6b63\u5e38\u72b6\u6001\u4e0d\u4e00\u81f4\u7684\u6a21\u5f0f\u3002<\/p>\n
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