{"id":6155,"date":"2024-06-18T16:45:42","date_gmt":"2024-06-18T08:45:42","guid":{"rendered":"https:\/\/t.n-years.com\/?p=6155"},"modified":"2024-06-18T16:45:42","modified_gmt":"2024-06-18T08:45:42","slug":"%e5%8f%98%e5%8c%96%e8%be%83%e5%a4%a7%e7%9a%84%e7%89%b9%e5%be%81%e5%80%bc%e5%a6%82%e4%bd%95%e4%bd%9c%e4%b8%ba%e4%b8%80%e4%b8%aa%e8%81%9a%e7%b1%bb%e4%bb%bb%e5%8a%a1%e7%9a%84%e7%89%b9%e5%be%81%e8%be%93","status":"publish","type":"post","link":"https:\/\/t.n-years.com\/?p=6155","title":{"rendered":"\u53d8\u5316\u8f83\u5927\u7684\u7279\u5f81\u503c\u5982\u4f55\u4f5c\u4e3a\u4e00\u4e2a\u805a\u7c7b\u4efb\u52a1\u7684\u7279\u5f81\u8f93\u5165"},"content":{"rendered":"\n

\u975e\u539f\u521b\u3001ChatGPT \u95ee\u7b54\u751f\u6210<\/p>\n\n\n\n

\u5c06\u7528\u6237\u7684\u968f\u673a\u8f93\u5165\u4f5c\u4e3a\u4e00\u4e2a\u805a\u7c7b\u4efb\u52a1\u7684\u7279\u5f81\u8f93\u5165\u9700\u8981\u51e0\u4e2a\u6b65\u9aa4\uff0c\u5177\u4f53\u53d6\u51b3\u4e8e\u8f93\u5165\u6570\u636e\u7684\u7c7b\u578b\u548c\u683c\u5f0f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u901a\u7528\u7684\u65b9\u6cd5\uff1a<\/p>\n\n\n\n

    \n
  1. \u6570\u636e\u6536\u96c6\u548c\u683c\u5f0f\u5316<\/strong>\uff1a\u6536\u96c6\u7528\u6237\u8f93\u5165\u7684\u6570\u636e\uff0c\u5e76\u5c06\u5176\u6574\u7406\u6210\u7ed3\u6784\u5316\u7684\u683c\u5f0f\uff0c\u5982\u8868\u683c\u6216\u6570\u636e\u6846\u3002<\/li>\n\n\n\n
  2. \u7279\u5f81\u63d0\u53d6\u548c\u8f6c\u6362<\/strong>\uff1a\u6839\u636e\u7528\u6237\u8f93\u5165\u7684\u7c7b\u578b\uff0c\u63d0\u53d6\u548c\u8f6c\u6362\u9002\u5f53\u7684\u7279\u5f81\u3002\u4f8b\u5982\uff0c\u6587\u672c\u8f93\u5165\u53ef\u4ee5\u8f6c\u6362\u6210\u6570\u503c\u7279\u5f81\uff08\u5982\u8bcd\u9891\u6216\u5d4c\u5165\u5411\u91cf\uff09\uff0c\u800c\u6570\u503c\u8f93\u5165\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528\u3002<\/li>\n\n\n\n
  3. \u6570\u636e\u9884\u5904\u7406<\/strong>\uff1a\u5bf9\u7279\u5f81\u6570\u636e\u8fdb\u884c\u6807\u51c6\u5316\u3001\u5f52\u4e00\u5316\u6216\u5176\u4ed6\u5fc5\u8981\u7684\u9884\u5904\u7406\u3002<\/li>\n\n\n\n
  4. \u6784\u5efa\u7279\u5f81\u77e9\u9635<\/strong>\uff1a\u5c06\u6240\u6709\u9884\u5904\u7406\u540e\u7684\u7279\u5f81\u6574\u5408\u5230\u4e00\u4e2a\u7279\u5f81\u77e9\u9635\u4e2d\uff0c\u4f5c\u4e3a\u805a\u7c7b\u7b97\u6cd5\u7684\u8f93\u5165\u3002<\/li>\n<\/ol>\n\n\n\n

    \u4e0b\u9762\u662f\u4e00\u4e9b\u5177\u4f53\u7684\u4f8b\u5b50\u548c\u4ee3\u7801\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u5904\u7406\u4e0d\u540c\u7c7b\u578b\u7684\u7528\u6237\u8f93\u5165\uff1a<\/p>\n\n\n\n

    \u4f8b\u5b501\uff1a\u6587\u672c\u8f93\u5165<\/h3>\n\n\n\n

    \u5047\u8bbe\u7528\u6237\u8f93\u5165\u7684\u662f\u4e00\u6bb5\u6587\u672c\uff0c\u53ef\u4ee5\u4f7f\u7528 TF-IDF \u6216\u8bcd\u5d4c\u5165\u6765\u63d0\u53d6\u7279\u5f81\u3002<\/p>\n\n\n\n

    import numpy as np\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.cluster import KMeans\n\n# \u5047\u8bbe\u7528\u6237\u8f93\u5165\u7684\u662f\u4e00\u4e2a\u6587\u672c\u5217\u8868\nuser_inputs = [\n    \"I love machine learning\",\n    \"Clustering algorithms are useful\",\n    \"I enjoy learning new things\",\n    \"KMeans is a popular clustering method\"\n]\n\n# \u4f7f\u7528 TF-IDF \u63d0\u53d6\u7279\u5f81\nvectorizer = TfidfVectorizer()\nX = vectorizer.fit_transform(user_inputs).toarray()\n\n# \u6807\u51c6\u5316\u6570\u636e\nscaler = StandardScaler()\nX_scaled = scaler.fit_transform(X)\n\n# \u4f7f\u7528 KMeans \u805a\u7c7b\nkmeans = KMeans(n_clusters=2, random_state=42)\nkmeans.fit(X_scaled)\n\n# \u83b7\u53d6\u805a\u7c7b\u6807\u7b7e\nlabels = kmeans.labels_\n\nprint(\"\u805a\u7c7b\u6807\u7b7e\uff1a\", labels)<\/code><\/pre>\n\n\n\n
    \u4f8b\u5b502\uff1a\u6570\u503c\u8f93\u5165<\/h3>\n\n\n\n
    \u5047\u8bbe\u7528\u6237\u8f93\u5165\u7684\u662f\u6570\u503c\u6570\u636e\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528\u8fd9\u4e9b\u6570\u503c\u4f5c\u4e3a\u7279\u5f81\u3002<\/p>\n\n\n\n
    import numpy as np\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.cluster import KMeans\n\n# \u5047\u8bbe\u7528\u6237\u8f93\u5165\u7684\u662f\u6570\u503c\u6570\u636e\uff0c\u5f62\u6210\u4e00\u4e2a numpy \u6570\u7ec4\nuser_inputs = np.array([\n    [1.0, 2.0, 3.0],\n    [4.0, 5.0, 6.0],\n    [7.0, 8.0, 9.0],\n    [10.0, 11.0, 12.0]\n])\n\n# \u6807\u51c6\u5316\u6570\u636e\nscaler = StandardScaler()\nX_scaled = scaler.fit_transform(user_inputs)\n\n# \u4f7f\u7528 KMeans \u805a\u7c7b\nkmeans = KMeans(n_clusters=2, random_state=42)\nkmeans.fit(X_scaled)\n\n# \u83b7\u53d6\u805a\u7c7b\u6807\u7b7e\nlabels = kmeans.labels_\n\nprint(\"\u805a\u7c7b\u6807\u7b7e\uff1a\", labels)<\/code><\/pre>\n\n\n\n
    \u4f8b\u5b503\uff1a\u6df7\u5408\u8f93\u5165<\/h3>\n\n\n\n
    \u5047\u8bbe\u7528\u6237\u8f93\u5165\u5305\u542b\u6587\u672c\u548c\u6570\u503c\u6570\u636e\uff0c\u9700\u8981\u5206\u522b\u5904\u7406\uff0c\u7136\u540e\u5c06\u7279\u5f81\u6574\u5408\u3002<\/p>\n\n\n\n
    import numpy as np\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.cluster import KMeans\nfrom scipy.sparse import hstack\n\n# \u5047\u8bbe\u7528\u6237\u8f93\u5165\u5305\u542b\u6587\u672c\u548c\u6570\u503c\u6570\u636e\ntexts = [\n    \"I love machine learning\",\n    \"Clustering algorithms are useful\",\n    \"I enjoy learning new things\",\n    \"KMeans is a popular clustering method\"\n]\nnumerical_data = np.array([\n    [1.0, 2.0],\n    [3.0, 4.0],\n    [5.0, 6.0],\n    [7.0, 8.0]\n])\n\n# \u6587\u672c\u7279\u5f81\u63d0\u53d6\nvectorizer = TfidfVectorizer()\ntext_features = vectorizer.fit_transform(texts)\n\n# \u6570\u503c\u6570\u636e\u6807\u51c6\u5316\nscaler = StandardScaler()\nnumerical_features = scaler.fit_transform(numerical_data)\n\n# \u5408\u5e76\u7279\u5f81\nX = hstack([text_features, numerical_features])\n\n# \u4f7f\u7528 KMeans \u805a\u7c7b\nkmeans = KMeans(n_clusters=2, random_state=42)\nkmeans.fit(X)\n\n# \u83b7\u53d6\u805a\u7c7b\u6807\u7b7e\nlabels = kmeans.labels_\n\nprint(\"\u805a\u7c7b\u6807\u7b7e\uff1a\", labels)<\/code><\/pre>\n\n\n\n
    \u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u53ef\u4ee5\u5c06\u7528\u6237\u7684\u968f\u673a\u8f93\u5165\u4f5c\u4e3a\u805a\u7c7b\u4efb\u52a1\u7684\u7279\u5f81\u8f93\u5165\uff0c\u5e76\u5e94\u7528 KMeans \u7b49\u805a\u7c7b\u7b97\u6cd5\u8fdb\u884c\u5206\u6790\u3002\u786e\u4fdd\u5728\u7279\u5f81\u63d0\u53d6\u548c\u9884\u5904\u7406\u65f6\u6839\u636e\u8f93\u5165\u6570\u636e\u7c7b\u578b\u8fdb\u884c\u9002\u5f53\u5904\u7406\uff0c\u4ee5\u83b7\u5f97\u6700\u4f73\u7684\u805a\u7c7b\u6548\u679c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
    \u975e\u539f\u521b\u3001ChatGPT \u95ee\u7b54\u751f\u6210 \u5c06\u7528\u6237\u7684\u968f\u673a\u8f93\u5165\u4f5c\u4e3a\u4e00\u4e2a\u805a\u7c7b\u4efb\u52a1\u7684\u7279\u5f81\u8f93\u5165\u9700\u8981\u51e0\u4e2a\u6b65\u9aa4\uff0c\u5177\u4f53\u53d6\u51b3\u4e8e\u8f93\u5165\u6570\u636e\u7684… <\/p>\n
    \u9605\u8bfb\u66f4\u591a<\/i><\/a><\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[79],"class_list":["post-6155","post","type-post","status-publish","format-standard","hentry","category-5","tag-79"],"_links":{"self":[{"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/posts\/6155","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/t.n-years.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6155"}],"version-history":[{"count":2,"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/posts\/6155\/revisions"}],"predecessor-version":[{"id":6157,"href":"https:\/\/t.n-years.com\/index.php?rest_route=\/wp\/v2\/posts\/6155\/revisions\/6157"}],"wp:attachment":[{"href":"https:\/\/t.n-years.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6155"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/t.n-years.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6155"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/t.n-years.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6155"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}