{"id":2587,"date":"2026-02-15T19:11:09","date_gmt":"2026-02-15T11:11:09","guid":{"rendered":"https:\/\/ai.ziyuanzz.online\/?page_id=2587"},"modified":"2026-03-28T09:37:09","modified_gmt":"2026-03-28T01:37:09","slug":"scikit-learn","status":"publish","type":"page","link":"https:\/\/ai.ziyuanzz.online\/index.php\/scikit-learn\/","title":{"rendered":"Scikit-learn"},"content":{"rendered":"
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\"\"<\/figure>\n<\/div>\n\n\n

Scikit-learn<\/h2>\n\n\n\n

Python\u673a\u5668\u5b66\u4e60\u5e93<\/p>\n\n\n\n

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\u8bbf\u95ee\u5b98\u7f51 ><\/a><\/div>\n<\/div>\n\n\n\n
<\/div>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/div>\n\n\n\n

Scikit-Learn\u662f\u4ec0\u4e48<\/h2>\n\n\n\n

Scikit-Learn \u662f Python \u673a\u5668\u5b66\u4e60\u5e93\uff0c\u5e7f\u6cdb\u5e94\u7528\u5728\u6570\u636e\u6316\u6398\u548c\u6570\u636e\u5206\u6790\u3002Scikit-Learn\u63d0\u4f9b\u7b80\u5355\u9ad8\u6548\u7684\u5de5\u5177\uff0c\u652f\u6301\u591a\u79cd\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5305\u62ec\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u548c\u964d\u7ef4\u7b49\u3002Scikit-Learn\u8bbe\u8ba1\u7b80\u6d01\u3001\u6613\u7528\uff0c\u4e14\u4e0e NumPy \u548c SciPy \u7b49\u79d1\u5b66\u8ba1\u7b97\u5e93\u65e0\u7f1d\u96c6\u6210\u3002Scikit-Learn \u4ee5\u5176\u5b9e\u7528\u6027\u3001\u9ad8\u6027\u80fd\u548c\u4e30\u5bcc\u7684\u7b97\u6cd5\u5b9e\u73b0\u800c\u95fb\u540d\uff0c\u9002\u5408\u4ece\u521d\u5b66\u8005\u5230\u4e13\u5bb6\u7684\u5404\u4e2a\u5c42\u6b21\u7684\u7528\u6237\u3002Scikit-Learn\u63d0\u4f9b\u8be6\u5c3d\u7684\u6587\u6863\u548c\u793a\u4f8b\uff0c\u5e2e\u52a9\u7528\u6237\u5feb\u901f\u4e0a\u624b\u5e76\u89e3\u51b3\u5b9e\u9645\u95ee\u9898\u3002<\/p>\n\n\n\n

\"Scikit-Learn\"<\/a><\/figure>\n\n\n\n

Scikit-Learn\u7684\u4e3b\u8981\u529f\u80fd<\/h2>\n\n\n\n
    \n
  • \u673a\u5668\u5b66\u4e60\u7b97\u6cd5<\/strong>\uff1a\u63d0\u4f9b\u591a\u79cd\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u548c\u964d\u7ef4\u7b97\u6cd5\uff0c\u6ee1\u8db3\u4e0d\u540c\u673a\u5668\u5b66\u4e60\u4efb\u52a1\u9700\u6c42\u3002<\/li>\n\n\n\n
  • \u6570\u636e\u9884\u5904\u7406<\/strong>\uff1a\u5305\u542b\u7279\u5f81\u7f29\u653e\u3001\u7f3a\u5931\u503c\u5904\u7406\u3001\u7279\u5f81\u7f16\u7801\u548c\u7279\u5f81\u9009\u62e9\u7b49\u5de5\u5177\uff0c\u5e2e\u52a9\u51c6\u5907\u6570\u636e\u4ee5\u4f9b\u6a21\u578b\u8bad\u7ec3\u3002<\/li>\n\n\n\n
  • \u6a21\u578b\u9009\u62e9\u4e0e\u8bc4\u4f30<\/strong>\uff1a\u63d0\u4f9b\u4ea4\u53c9\u9a8c\u8bc1\u3001\u8d85\u53c2\u6570\u8c03\u4f18\u548c\u6027\u80fd\u8bc4\u4f30\u5de5\u5177\uff0c\u5e2e\u52a9\u9009\u62e9\u548c\u4f18\u5316\u6a21\u578b\u3002<\/li>\n\n\n\n
  • \u6d41\u6c34\u7ebf\uff08Pipeline\uff09<\/strong>\uff1a\u901a\u8fc7\u6d41\u6c34\u7ebf\u5de5\u5177\u5c06\u6570\u636e\u9884\u5904\u7406\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u7ec4\u5408\u6210\u4e00\u4e2a\u5b8c\u6574\u7684\u6d41\u7a0b\uff0c\u7b80\u5316\u4ee3\u7801\u5e76\u63d0\u9ad8\u6548\u7387\u3002<\/li>\n\n\n\n
  • \u96c6\u6210\u5b66\u4e60<\/strong>\uff1a\u63d0\u4f9b Bagging\u3001Boosting \u548c\u968f\u673a\u68ee\u6797\u7b49\u96c6\u6210\u5b66\u4e60\u7b97\u6cd5\uff0c\u63d0\u5347\u6a21\u578b\u7684\u6027\u80fd\u548c\u7a33\u5b9a\u6027\u3002<\/li>\n\n\n\n
  • \u591a\u8f93\u51fa\u4e0e\u591a\u6807\u7b7e<\/strong>\uff1a\u652f\u6301\u591a\u8f93\u51fa\u5206\u7c7b\u548c\u56de\u5f52\u4efb\u52a1\uff0c\u53ca\u591a\u6807\u7b7e\u5206\u7c7b\u4efb\u52a1\uff0c\u652f\u6301\u6a21\u578b\u540c\u65f6\u9884\u6d4b\u591a\u4e2a\u76ee\u6807\u503c\u6216\u7c7b\u522b\u3002<\/li>\n<\/ul>\n\n\n\n

    \u5982\u4f55\u4f7f\u7528Scikit-Learn<\/h2>\n\n\n\n
      \n
    • \u5b89\u88c5 scikit-learn<\/strong>\uff1a\n
        \n
      • \u4f7f\u7528 pip \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
        pip <span class<\/strong>=\"token function\">install<\/span> <span class<\/strong>=\"token parameter variable\">-U<\/span> scikit-learn<\/pre>\n\n\n\n
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        • \n
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          • \u4f7f\u7528 conda \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
            conda <span class<\/strong>=\"token function\">install<\/span> <span class<\/strong>=\"token parameter variable\">-c<\/span> conda-forge scikit-learn<\/pre>\n\n\n\n
              \n
            • \u5bfc\u5165\u5fc5\u8981\u7684\u6a21\u5757<\/strong>\uff1a\u5728 Python \u4e2d\uff0c\u5bfc\u5165 scikit-learn \u53ca\u76f8\u5173\u7684\u6a21\u5757\uff08\u5982 NumPy \u548c Pandas\uff09\u5904\u7406\u6570\u636e\u3002<\/li>\n<\/ul>\n\n\n\n
              <span class<\/strong>=\"token keyword\">import<\/span> numpy <span class<\/strong>=\"token keyword\">as<\/span> np<span class<\/strong>=\"token keyword\">import<\/span> pandas <span class<\/strong>=\"token keyword\">as<\/span> pd<span class<\/strong>=\"token keyword\">from<\/span> sklearn <span class<\/strong>=\"token keyword\">import<\/span> datasets<span class<\/strong>=\"token keyword\">from<\/span> sklearn<span class<\/strong>=\"token punctuation\">.<\/span>model_selection <span class<\/strong>=\"token keyword\">import<\/span> train_test_split<span class<\/strong>=\"token keyword\">from<\/span> sklearn<span class<\/strong>=\"token punctuation\">.<\/span>preprocessing <span class<\/strong>=\"token keyword\">import<\/span> StandardScaler<span class<\/strong>=\"token keyword\">from<\/span> sklearn<span class<\/strong>=\"token punctuation\">.<\/span>linear_model <span class<\/strong>=\"token keyword\">import<\/span> LogisticRegression<span class<\/strong>=\"token keyword\">from<\/span> sklearn<span class<\/strong>=\"token punctuation\">.<\/span>metrics <span class<\/strong>=\"token keyword\">import<\/span> accuracy_score<span class<\/strong>=\"token punctuation\">,<\/span> classification_report<\/pre>\n\n\n\n
                \n
              • \u52a0\u8f7d\u6570\u636e\u96c6<\/strong>\uff1ascikit-learn \u63d0\u4f9b\u8bb8\u591a\u5185\u7f6e\u7684\u6570\u636e\u96c6\uff0c\u4f8b\u5982\u9e22\u5c3e\u82b1\u6570\u636e\u96c6\uff08Iris\uff09\u3001\u624b\u5199\u6570\u5b57\u6570\u636e\u96c6\uff08Digits\uff09\u7b49\u3002<\/li>\n\n\n\n
              • \n
                  \n
                • \u4f7f\u7528\u5185\u7f6e\u6570\u636e\u96c6<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
                  <span class<\/strong>=\"token comment\"># \u52a0\u8f7d\u9e22\u5c3e\u82b1\u6570\u636e\u96c6<\/span>iris <span class<\/strong>=\"token operator\">=<\/span> datasets<span class<\/strong>=\"token punctuation\">.<\/span>load_iris<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token punctuation\">)<\/span>X <span class<\/strong>=\"token operator\">=<\/span> iris<span class<\/strong>=\"token punctuation\">.<\/span>datay <span class<\/strong>=\"token operator\">=<\/span> iris<span class<\/strong>=\"token punctuation\">.<\/span>target<\/pre>\n\n\n\n
                    \n
                  • \n
                      \n
                    • \u52a0\u8f7d\u81ea\u5b9a\u4e49\u6570\u636e\u96c6<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
                      <span class<\/strong>=\"token comment\"># \u4f7f\u7528 Pandas \u52a0\u8f7d CSV \u6587\u4ef6<\/span>data <span class<\/strong>=\"token operator\">=<\/span> pd<span class<\/strong>=\"token punctuation\">.<\/span>read_csv<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token string\">'your_dataset.csv'<\/span><span class<\/strong>=\"token punctuation\">)<\/span>X <span class<\/strong>=\"token operator\">=<\/span> data<span class<\/strong>=\"token punctuation\">.<\/span>drop<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token string\">'target_column'<\/span><span class<\/strong>=\"token punctuation\">,<\/span> axis<span class<\/strong>=\"token operator\">=<\/span><span class<\/strong>=\"token number\">1<\/span><span class<\/strong>=\"token punctuation\">)<\/span>y <span class<\/strong>=\"token operator\">=<\/span> data<span class<\/strong>=\"token punctuation\">[<\/span><span class<\/strong>=\"token string\">'target_column'<\/span><span class<\/strong>=\"token punctuation\">]<\/span><\/pre>\n\n\n\n
                        \n
                      • \u6570\u636e\u9884\u5904\u7406<\/strong>\uff1a\u5728\u8bad\u7ec3\u6a21\u578b\u4e4b\u524d\uff0c\u901a\u5e38\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u5904\u7406\uff0c\u4f8b\u5982\u5212\u5206\u8bad\u7ec3\u96c6\u548c\u6d4b\u8bd5\u96c6\u3001\u6807\u51c6\u5316\u7b49\u3002<\/li>\n<\/ul>\n\n\n\n
                        X_train<span class<\/strong>=\"token punctuation\">,<\/span> X_test<span class<\/strong>=\"token punctuation\">,<\/span> y_train<span class<\/strong>=\"token punctuation\">,<\/span> y_test <span class<\/strong>=\"token operator\">=<\/span> train_test_split<span class<\/strong>=\"token punctuation\">(<\/span>X<span class<\/strong>=\"token punctuation\">,<\/span> y<span class<\/strong>=\"token punctuation\">,<\/span> test_size<span class<\/strong>=\"token operator\">=<\/span><span class<\/strong>=\"token number\">0.2<\/span><span class<\/strong>=\"token punctuation\">,<\/span> random_state<span class<\/strong>=\"token operator\">=<\/span><span class<\/strong>=\"token number\">42<\/span><span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                          \n
                        • \u6807\u51c6\u5316\u6570\u636e<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
                          scaler <span class<\/strong>=\"token operator\">=<\/span> StandardScaler<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token punctuation\">)<\/span>X_train <span class<\/strong>=\"token operator\">=<\/span> scaler<span class<\/strong>=\"token punctuation\">.<\/span>fit_transform<span class<\/strong>=\"token punctuation\">(<\/span>X_train<span class<\/strong>=\"token punctuation\">)<\/span>X_test <span class<\/strong>=\"token operator\">=<\/span> scaler<span class<\/strong>=\"token punctuation\">.<\/span>transform<span class<\/strong>=\"token punctuation\">(<\/span>X_test<span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                            \n
                          • \u8bad\u7ec3\u6a21\u578b<\/strong>\uff1a\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u5e76\u8bad\u7ec3\u5b83\u3002\u4ee5\u903b\u8f91\u56de\u5f52\u4e3a\u4f8b\u3002<\/li>\n<\/ul>\n\n\n\n
                            model <span class<\/strong>=\"token operator\">=<\/span> LogisticRegression<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token punctuation\">)<\/span>model<span class<\/strong>=\"token punctuation\">.<\/span>fit<span class<\/strong>=\"token punctuation\">(<\/span>X_train<span class<\/strong>=\"token punctuation\">,<\/span> y_train<span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                              \n
                            • \u6a21\u578b\u8bc4\u4f30<\/strong>\uff1a\u4f7f\u7528\u6d4b\u8bd5\u96c6\u8bc4\u4f30\u6a21\u578b\u7684\u6027\u80fd\u3002<\/li>\n<\/ul>\n\n\n\n
                              y_pred <span class<\/strong>=\"token operator\">=<\/span> model<span class<\/strong>=\"token punctuation\">.<\/span>predict<span class<\/strong>=\"token punctuation\">(<\/span>X_test<span class<\/strong>=\"token punctuation\">)<\/span>accuracy <span class<\/strong>=\"token operator\">=<\/span> accuracy_score<span class<\/strong>=\"token punctuation\">(<\/span>y_test<span class<\/strong>=\"token punctuation\">,<\/span> y_pred<span class<\/strong>=\"token punctuation\">)<\/span><span class<\/strong>=\"token keyword\">print<\/span><span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token string-interpolation\"><span class<\/strong>=\"token string\">f'Accuracy: <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>accuracy<span class=\"token punctuation\">:<\/span><span class=\"token format-spec\">.2f<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\">'<\/span><\/span><span class<\/strong>=\"token punctuation\">)<\/span><span class<\/strong>=\"token keyword\">print<\/span><span class<\/strong>=\"token punctuation\">(<\/span>classification_report<span class<\/strong>=\"token punctuation\">(<\/span>y_test<span class<\/strong>=\"token punctuation\">,<\/span> y_pred<span class<\/strong>=\"token punctuation\">)<\/span><span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                                \n
                              • \u4f7f\u7528\u6a21\u578b\u8fdb\u884c\u9884\u6d4b<\/strong>\uff1a\u5728\u65b0\u6570\u636e\u4e0a\u4f7f\u7528\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u8fdb\u884c\u9884\u6d4b\u3002<\/li>\n<\/ul>\n\n\n\n
                                new_data <span class<\/strong>=\"token operator\">=<\/span> np<span class<\/strong>=\"token punctuation\">.<\/span>array<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token punctuation\">[<\/span><span class<\/strong>=\"token punctuation\">[<\/span><span class<\/strong>=\"token number\">5.1<\/span><span class<\/strong>=\"token punctuation\">,<\/span> <span class<\/strong>=\"token number\">3.5<\/span><span class<\/strong>=\"token punctuation\">,<\/span> <span class<\/strong>=\"token number\">1.4<\/span><span class<\/strong>=\"token punctuation\">,<\/span> <span class<\/strong>=\"token number\">0.2<\/span><span class<\/strong>=\"token punctuation\">]<\/span><span class<\/strong>=\"token punctuation\">]<\/span><span class<\/strong>=\"token punctuation\">)<\/span>  <span class<\/strong>=\"token comment\"># \u793a\u4f8b\u65b0\u6570\u636e<\/span>new_data <span class<\/strong>=\"token operator\">=<\/span> scaler<span class<\/strong>=\"token punctuation\">.<\/span>transform<span class<\/strong>=\"token punctuation\">(<\/span>new_data<span class<\/strong>=\"token punctuation\">)<\/span>  <span class<\/strong>=\"token comment\"># \u6807\u51c6\u5316<\/span>prediction <span class<\/strong>=\"token operator\">=<\/span> model<span class<\/strong>=\"token punctuation\">.<\/span>predict<span class<\/strong>=\"token punctuation\">(<\/span>new_data<span class<\/strong>=\"token punctuation\">)<\/span><span class<\/strong>=\"token keyword\">print<\/span><span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token string-interpolation\"><span class<\/strong>=\"token string\">f'Prediction: <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>prediction<span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\">'<\/span><\/span><span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                                  \n
                                • \u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b<\/strong>\uff1a\n
                                    \n
                                  • \u4fdd\u5b58\u6a21\u578b<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
                                    <span class<\/strong>=\"token keyword\">import<\/span> joblibjoblib<span class<\/strong>=\"token punctuation\">.<\/span>dump<span class<\/strong>=\"token punctuation\">(<\/span>model<span class<\/strong>=\"token punctuation\">,<\/span> <span class<\/strong>=\"token string\">'model.pkl'<\/span><span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                                      \n
                                    • \n
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                                      • \u52a0\u8f7d\u6a21\u578b<\/strong>\uff1a<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
                                        model <span class<\/strong>=\"token operator\">=<\/span> joblib<span class<\/strong>=\"token punctuation\">.<\/span>load<span class<\/strong>=\"token punctuation\">(<\/span><span class<\/strong>=\"token string\">'model.pkl'<\/span><span class<\/strong>=\"token punctuation\">)<\/span><\/pre>\n\n\n\n
                                        Scikit-Learn\u7684\u5e94\u7528\u573a\u666f<\/h2>\n\n\n\n
                                          \n
                                        • \u6570\u636e\u6316\u6398<\/strong>\uff1a\u4ece\u5927\u91cf\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u4ef7\u503c\u7684\u4fe1\u606f\uff0c\u4f8b\u5982\u901a\u8fc7\u805a\u7c7b\u7b97\u6cd5\u53d1\u73b0\u6570\u636e\u4e2d\u7684\u81ea\u7136\u5206\u7ec4\u3002<\/li>\n\n\n\n
                                        • \u6570\u636e\u5206\u6790<\/strong>\uff1a\u5e2e\u52a9\u8fdb\u884c\u6570\u636e\u7684\u63a2\u7d22\u6027\u5206\u6790\uff0c\u4f8b\u5982\u7528\u964d\u7ef4\u7b97\u6cd5\uff08\u5982 PCA\uff09\u53ef\u89c6\u5316\u9ad8\u7ef4\u6570\u636e\u3002<\/li>\n\n\n\n
                                        • \u5206\u7c7b\u4efb\u52a1<\/strong>\uff1a\u9002\u7528\u5404\u79cd\u5206\u7c7b\u95ee\u9898\uff0c\u5982\u5783\u573e\u90ae\u4ef6\u68c0\u6d4b\u3001\u56fe\u50cf\u5206\u7c7b\u3001\u75be\u75c5\u8bca\u65ad\u7b49\u3002<\/li>\n\n\n\n
                                        • \u56de\u5f52\u4efb\u52a1<\/strong>\uff1a\u7528\u5728\u9884\u6d4b\u8fde\u7eed\u503c\uff0c\u4f8b\u5982\u623f\u4ef7\u9884\u6d4b\u3001\u80a1\u7968\u4ef7\u683c\u9884\u6d4b\u3001\u9500\u552e\u91cf\u9884\u6d4b\u7b49\u3002<\/li>\n\n\n\n
                                        • \u805a\u7c7b\u5206\u6790<\/strong>\uff1a\u57fa\u4e8e\u65e0\u76d1\u7763\u5b66\u4e60\u7b97\u6cd5\uff08\u5982 K-\u5747\u503c\uff09\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff0c\u53d1\u73b0\u6570\u636e\u4e2d\u7684\u6a21\u5f0f\u548c\u7ed3\u6784\u3002<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
                                          Scikit-learn Python\u673a\u5668\u5b66\u4e60\u5e93 Scikit-Learn\u662f\u4ec0\u4e48 Scikit-Learn \u662f […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2587","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/pages\/2587","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/comments?post=2587"}],"version-history":[{"count":0,"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/pages\/2587\/revisions"}],"wp:attachment":[{"href":"https:\/\/ai.ziyuanzz.online\/index.php\/wp-json\/wp\/v2\/media?parent=2587"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}