{"id":3182,"date":"2022-02-27T12:56:25","date_gmt":"2022-02-27T04:56:25","guid":{"rendered":"https:\/\/egonlin.com\/?p=3182"},"modified":"2022-02-27T12:56:25","modified_gmt":"2022-02-27T04:56:25","slug":"%e7%ac%ac%e4%b8%89%e7%af%87%ef%bc%9ascikit-learn%e5%ba%93%e4%b9%8b%e9%9a%8f%e6%9c%ba%e6%a3%ae%e6%9e%97","status":"publish","type":"post","link":"https:\/\/egonlin.com\/?p=3182","title":{"rendered":"\u7b2c\u4e09\u7bc7\uff1ascikit-learn\u5e93\u4e4b\u968f\u673a\u68ee\u6797"},"content":{"rendered":"<h1>scikit-learn\u5e93\u4e4b\u968f\u673a\u68ee\u6797<\/h1>\n<p>&emsp;&emsp;\u672c\u6587\u4e3b\u8981\u4ecb\u7ecd\u968f\u673a\u68ee\u6797\u7684\u4e24\u4e2a\u6a21\u578b<code>RandomForestClassifier<\/code>\u548c<code>RandomForestRegressor<\/code>\uff0c\u8fd9\u4e24\u4e2a\u6a21\u578b\u8c03\u53c2\u5305\u62ec\u4e24\u90e8\u5206\uff0c\u7b2c\u4e00\u90e8\u5206\u662fBagging\u6846\u67b6\uff0c\u7b2c\u4e8c\u90e8\u5206\u662fCART\u51b3\u7b56\u6811\u7684\u53c2\u6570\u3002\u672c\u6587\u4f1a\u8be6\u89e3\u4ecb\u7ecd<code>RandomForestClassifier<\/code>\u6a21\u578b\uff0c\u7136\u540e\u4f1a\u5bf9\u6bd4\u7740\u8bb2\u89e3<code>RandomForestRegressor<\/code>\u6a21\u578b\u3002<\/p>\n<p>&emsp;&emsp;\u63a5\u4e0b\u6765\u5c06\u4f1a\u8ba8\u8bba\u4e0a\u8ff0\u4e24\u8005\u7684\u533a\u522b\uff0c\u7531\u4e8e\u662f\u4ece\u5b98\u65b9\u6587\u6863\u7ffb\u8bd1\u800c\u6765\uff0c\u7ffb\u8bd1\u4f1a\u7565\u6709\u504f\u9887\uff0c\u6709\u5174\u8da3\u7684\u4e5f\u53ef\u4ee5\u53bbscikit-learn\u5b98\u65b9\u6587\u6863\u67e5\u770bhttps:\/\/scikit-learn.org\/stable\/modules\/classes.html#module-sklearn.ensemble<\/p>\n<h1>RandomForestClassifier<\/h1>\n<h2>\u4f7f\u7528\u573a\u666f<\/h2>\n<p>&emsp;&emsp;<code>RandomForestClassfier<\/code>\u6a21\u578b\u4e3b\u8981\u89e3\u51b3\u5206\u7c7b\u95ee\u9898\uff0c\u5176\u4ed6\u4e5f\u6ca1\u5565\u597d\u8bf4\u7684\u3002<\/p>\n<h2>\u4ee3\u7801<\/h2>\n<pre><code class=\"language-python\">from sklearn.ensemble import RandomForestClassifier\nfrom sklearn.datasets import make_classification\n\nX, y = make_classification(n_samples=1000, n_features=4,\n                           n_informative=2, n_redundant=0, random_state=0, shuffle=False)<\/code><\/pre>\n<pre><code class=\"language-python\">clf = RandomForestClassifier(n_estimators=100, max_depth=2, random_state=0)\nclf.fit(X, y)<\/code><\/pre>\n<pre><code>RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n            max_depth=2, max_features='auto', max_leaf_nodes=None,\n            min_impurity_decrease=0.0, min_impurity_split=None,\n            min_samples_leaf=1, min_samples_split=2,\n            min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=None,\n            oob_score=False, random_state=0, verbose=0, warm_start=False)<\/code><\/pre>\n<pre><code class=\"language-python\">print(clf.feature_importances_)<\/code><\/pre>\n<pre><code>[0.14205973 0.76664038 0.0282433  0.06305659]<\/code><\/pre>\n<pre><code class=\"language-python\">print(clf.predict([[0, 0, 0, 0]]))<\/code><\/pre>\n<pre><code>[1]<\/code><\/pre>\n<h2>\u53c2\u6570<\/h2>\n<ul>\n<li><strong>n_estimators\uff1a<\/strong>\uff1a\u5f31\u5b66\u4e60\u5668\u4e2a\u6570\uff0cint\u7c7b\u578b\u3002\u5f31\u5b66\u4e60\u7684\u4e2a\u6570\uff0c\u4e5f\u53ef\u4ee5\u8bf4\u662f\u5f31\u5b66\u4e60\u5668\u7684\u6700\u5927\u8fed\u4ee3\u6b21\u6570\u3002\u9ed8\u8ba4\u4e3a10\u3002<\/li>\n<li><strong>criterion\uff1a<\/strong>\u7279\u5f81\u9009\u62e9\uff0cstr\u7c7b\u578b\u3002criterion=&#8217;gini&#8217;\u8868\u793a\u57fa\u5c3c\u6307\u6570\uff1bcriterion=&#8217;entropy&#8217;\u8868\u793a\u4fe1\u606f\u589e\u76ca\uff0c\u63a8\u8350\u4f7f\u7528&#8217;gini&#8217;\u3002\u9ed8\u8ba4\u4e3a&#8217;gini&#8217;\u3002<\/li>\n<li><strong>splitter\uff1a<\/strong>\u7279\u5f81\u5212\u5206\u70b9\u9009\u62e9\uff0cstr\u7c7b\u578b\u3002splitter=&#8217;best&#8217;\u5728\u7279\u5f81\u7684\u6240\u6709\u5212\u5206\u70b9\u4e2d\u627e\u51fa\u6700\u4f18\u7684\u5212\u5206\u70b9\uff0c\u9002\u5408\u5c0f\u6837\u672c\u91cf\uff1bsplitter=&#8217;random&#8217;\u968f\u673a\u7684\u5728\u90e8\u5206\u5212\u5206\u70b9\u4e2d\u627e\u5230\u5c40\u90e8\u6700\u4f18\u7684\u5212\u5206\u70b9\uff0c\u9002\u5408\u5927\u6837\u672c\u91cf\u3002\u9ed8\u8ba4\u4e3a&#8217;best&#8217;\u3002<\/li>\n<li><strong>max_depth\uff1a<\/strong>\u6700\u5927\u6df1\u5ea6\uff0cint\u7c7b\u578b\u3002\u5982\u679c\u6837\u672c\u7279\u5f81\u6570\u8f83\u5c11\u53ef\u4ee5\u4f7f\u7528\u9ed8\u8ba4\u503c\uff0c\u5982\u679c\u6837\u672c\u7279\u5f81\u6570\u8f83\u591a\u4e00\u822c\u7528max_depty=10-100\u9650\u5236\u6811\u7684\u6700\u5927\u6df1\u5ea6\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<li><strong>min_samples_split\uff1a<\/strong>\u5185\u90e8\u8282\u70b9\u5212\u5206\u9700\u8981\u6700\u5c11\u6837\u672c\u6570\uff0cfloat\u7c7b\u578b\u3002\u9650\u5b9a\u5b50\u6811\u7ee7\u7eed\u5212\u5206\u7684\u6761\u4ef6\uff0c\u5982\u679c\u67d0\u8282\u70b9\u7684\u6837\u672c\u6570\u5c11\u4e8emin_samples_split\uff0c\u5219\u4f1a\u505c\u6b62\u7ee7\u7eed\u5212\u5206\u5b50\u6811\u3002\u5982\u679c\u6837\u672c\u6570\u91cf\u8fc7\u5927\uff0c\u5efa\u8bae\u589e\u5927\u8be5\u503c\uff0c\u5426\u5219\u5efa\u8bae\u4f7f\u7528\u9ed8\u8ba4\u503c\u3002\u9ed8\u8ba4\u4e3a2\u3002<\/li>\n<li><strong>min_samples_leaf\uff1a<\/strong>\u53f6\u5b50\u8282\u70b9\u6700\u5c11\u6837\u672c\u6570float\u7c7b\u578b\u3002\u5982\u679c\u5728\u67d0\u6b21\u5212\u5206\u53f6\u5b50\u8282\u70b9\u6570\u76ee\u5c0f\u4e8e\u6837\u672c\u6570\uff0c\u5219\u4f1a\u548c\u5144\u5f1f\u8282\u70b9\u4e00\u8d77\u526a\u679d\u3002\u5982\u679c\u6837\u672c\u6570\u91cf\u8fc7\u5927\uff0c\u5efa\u8bae\u589e\u5927\u8be5\u503c\uff0c\u5426\u5219\u5efa\u8bae\u4f7f\u7528\u9ed8\u8ba4\u503c\u3002\u9ed8\u8ba4\u4e3a1\u3002<\/li>\n<li><strong>min_weight_fraction_leaf\uff1a<\/strong>\u53f6\u5b50\u8282\u70b9\u6700\u5c0f\u7684\u6837\u672c\u6743\u91cd\u548c\uff0cfloat\u7c7b\u578b\u3002\u8be5\u53c2\u6570\u9650\u5236\u4e86\u53f6\u5b50\u8282\u70b9\u6240\u6709\u6837\u672c\u6743\u91cd\u548c\u7684\u6700\u5c0f\u503c\uff0c\u5982\u679c\u5c0f\u4e8e\u8be5\u503c\uff0c\u5219\u4f1a\u548c\u5144\u5f1f\u8282\u70b9\u4e00\u8d77\u526a\u679d\u3002\u5982\u679c\u6837\u672c\u6709\u89d2\u5ea6\u7684\u7f3a\u5931\u503c\uff0c\u6216\u8005\u6837\u672c\u7684\u5206\u5e03\u504f\u5dee\u8f83\u5927\uff0c\u5219\u53ef\u4ee5\u8003\u8651\u6743\u91cd\u95ee\u9898\u3002\u9ed8\u8ba4\u4e3a0\u3002<\/li>\n<li><strong>max_features\uff1a<\/strong>\u5212\u5206\u7684\u6700\u5927\u7279\u5f81\u6570\uff0cstr\u3001int\u3001float\u7c7b\u578b\u3002max_depth=&#8217;log2&#8217;\u8868\u793a\u6700\u591a\u8003\u8651$log_2n$\u4e2a\u7279\u5f81\uff1bmax_depth={&#8216;sqrt&#8217;,&#8217;auto&#8217;}\u8868\u793a\u6700\u591a\u8003\u8651$\\sqrt{n}$\u4e2a\u7279\u5f81\uff1bmax_depth=int\u7c7b\u578b\uff0c\u8003\u8651$|int\u7c7b\u578b|$\u4e2a\u7279\u5f81\uff1bmax_depth=float\u7c7b\u578b\uff0c\u59820.3\uff0c\u5219\u8003\u8651$0.3n$\u4e2a\u7279\u5f81\uff0c\u5176\u4e2d$n$\u4e3a\u6837\u672c\u603b\u7279\u5f81\u6570\u3002\u9ed8\u8ba4\u4e3aNone\uff0c\u6837\u672c\u7279\u5f81\u6570\u4e0d\u5927\u4e8e50\u63a8\u8350\u4f7f\u7528\u9ed8\u8ba4\u503c\u3002<\/li>\n<li><strong>max_leaf_nodes\uff1a<\/strong>\u6700\u5927\u53f6\u5b50\u8282\u70b9\u6570\uff0cint\u7c7b\u578b\u3002\u9650\u5236\u6700\u5927\u53f6\u5b50\u8282\u70b9\u6570\uff0c\u53ef\u4ee5\u9632\u6b62\u6811\u8fc7\u6df1\uff0c\u56e0\u6b64\u53ef\u4ee5\u9632\u6b62\u8fc7\u62df\u5408\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<li><strong>min_impurity_decrease\uff1a<\/strong>\u8282\u70b9\u51cf\u5c0f\u4e0d\u7eaf\u5ea6\uff0cfloat\u7c7b\u578b\u3002\u5982\u679c\u67d0\u8282\u70b9\u5212\u5206\u4f1a\u5bfc\u81f4\u4e0d\u7eaf\u5ea6\u7684\u51cf\u5c11\u5927\u4e8emin_impurity_decrease\uff0c\u5219\u505c\u6b62\u8be5\u8282\u70b9\u5212\u5206\u3002\u9ed8\u8ba4\u4e3a0\u3002<\/li>\n<li><strong>min_impurity_split\uff1a<\/strong>\u8282\u70b9\u5212\u5206\u6700\u5c0f\u4e0d\u7eaf\u5ea6\uff0cfloat\u7c7b\u578b\u3002\u5982\u679c\u67d0\u8282\u70b9\u7684\u4e0d\u7eaf\u5ea6\u5c0f\u4e8emin_impurity_split\uff0c\u5219\u505c\u6b62\u8be5\u8282\u70b9\u5212\u5206\uff0c\u5373\u4e0d\u751f\u6210\u53f6\u5b50\u8282\u70b9\u3002\u9ed8\u8ba4\u4e3a1e-7(0.0000001)\u3002<\/li>\n<li><strong>class_weight\uff1a<\/strong>\u7c7b\u522b\u6743\u91cd\uff0cdict\u7c7b\u578b\u6216str\u7c7b\u578b\u3002\u5bf9\u4e8e\u4e8c\u5143\u5206\u7c7b\u95ee\u9898\u53ef\u4ee5\u4f7f\u7528class_weight={0:0.9,1:0.1}\uff0c\u8868\u793a0\u7c7b\u522b\u6743\u91cd\u4e3a0.9\uff0c1\u7c7b\u522b\u6743\u91cd\u4e3a0.1\uff0cstr\u7c7b\u578b\u5373\u4e3a&#8217;balanced&#8217;\uff0c\u6a21\u578b\u5c06\u6839\u636e\u8bad\u7ec3\u96c6\u81ea\u52a8\u4fee\u6539\u4e0d\u540c\u7c7b\u522b\u7684\u6743\u91cd\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<li><strong>bootstrp\uff1a<\/strong>bool\u7c7b\u578b\u3002\u9ed8\u8ba4\u4e3aTrue\u3002\u6784\u5efa\u51b3\u7b56\u6811\u65f6\u662f\u5426\u5f15\u5bfc\u6837\u672c\u3002<\/li>\n<li><strong>oob_score\uff1a<\/strong>\u888b\u5916\u6a21\u578b\uff0cbool\u7c7b\u578b\u3002\u662f\u5426\u91c7\u7528\u888b\u5916\u6837\u672c\u6765\u8bc4\u4f30\u6a21\u578b\u7684\u597d\u574f\uff0c\u4e2a\u4eba\u63a8\u8350\u8bbe\u7f6e\u4e3aTrue\uff0c\u56e0\u4e3a\u888b\u5916\u5206\u6570\u53cd\u5e94\u4e86\u4e00\u4e2a\u6a21\u578b\u62df\u5408\u540e\u7684\u6cdb\u5316\u80fd\u529b\u3002\u9ed8\u8ba4\u4e3aFalse\u3002<\/li>\n<li><strong>n_jobs\uff1a<\/strong>\u5e76\u884c\u6570\uff0cint\u7c7b\u578b\u3002n_jobs=1\u4f7f\u75281\u4e2acpu\u8fd0\u884c\u7a0b\u5e8f\uff1bn_jobs=2\uff0c\u4f7f\u75282\u4e2acpu\u8fd0\u884c\u7a0b\u5e8f\uff1bn_jobs=-1\uff0c\u4f7f\u7528\u6240\u6709cpu\u8fd0\u884c\u7a0b\u5e8f\u3002\u9ed8\u8ba4\u4e3a1\u3002<\/li>\n<li><strong>random_state\uff1a<\/strong>\u968f\u673a\u6570\u79cd\u5b50\uff0cint\u7c7b\u578b\u3002random_state=None\uff0c\u4e0d\u540c\u65f6\u523b\u4ea7\u751f\u7684\u968f\u673a\u6570\u636e\u662f\u4e0d\u540c\u7684\uff1brandom_state=int\u7c7b\u578b\uff0c\u76f8\u540c\u968f\u673a\u6570\u79cd\u5b50\u4e0d\u540c\u65f6\u523b\u4ea7\u751f\u7684\u968f\u673a\u6570\u662f\u76f8\u540c\u7684\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<li><strong>verbose\uff1a<\/strong>\u65e5\u5fd7\u5197\u957f\u5ea6\uff0cint\u7c7b\u578b\u3002verbose=0\uff0c\u4e0d\u8f93\u51fa\u8bad\u7ec3\u8fc7\u7a0b\uff1bverbose=1\uff0c\u8f93\u51fa\u90e8\u5206\u8bad\u7ec3\u8fc7\u7a0b\uff1bverbose&gt;1\uff0c\u8f93\u51fa\u6240\u6709\u7684\u8bad\u7ec3\u8fc7\u7a0b\u3002\u9ed8\u8ba4\u4e3a0\u3002<\/li>\n<li><strong>warm_start\uff1a<\/strong>\u70ed\u542f\u52a8\uff0cbool\u7c7b\u578b\u3002\u5982\u679c\u4e3aTrue\uff0c\u5219\u57fa\u4e8e\u4e0a\u4e00\u4e2a\u968f\u673a\u68ee\u6797\u6dfb\u52a0\u51b3\u7b56\u6811\uff1b\u5982\u679c\u4e3aFalse\uff0c\u5219\u91cd\u65b0\u751f\u6210\u4e00\u4e2a\u968f\u673a\u68ee\u6797\u3002\u9ed8\u8ba4\u4e3aFalse\u3002<\/li>\n<li><strong>class_weight\uff1a<\/strong>\u6837\u672c\u7c7b\u522b\u6743\u91cd\uff0c{dict\u7c7b\u578b,&#8217;balanced&#8217;}\u3002\u7ed9\u6bcf\u4e2a\u7c7b\u522b\u6307\u5b9a\u4e0d\u540c\u7684\u6743\u91cd\uff0c&#8217;balanced&#8217;\u5c06\u81ea\u52a8\u5206\u914d\u4e0d\u540c\u7c7b\u522b\u6837\u672c\u7684\u6743\u91cd\u3002\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n<\/ul>\n<h2>\u5c5e\u6027<\/h2>\n<ul>\n<li><strong>estimators_\uff1a<\/strong>list\u7c7b\u578b\u3002\u6240\u6709\u51b3\u7b56\u6811\u96c6\u5408\u3002<\/li>\n<li><strong>classes_\uff1a<\/strong>array\u7c7b\u578b\u3002\u6240\u6709\u7c7b\u522b\u5217\u8868\u3002<\/li>\n<li><strong>n<em>classes<\/em>\uff1a<\/strong>int\u7c7b\u578b\u3002\u7c7b\u522b\u4e2a\u6570\u3002<\/li>\n<li><strong>n<em>features<\/em>\uff1a<\/strong>int\u7c7b\u578b\u3002\u7279\u5f81\u4e2a\u6570\u3002<\/li>\n<li><strong>n<em>outputs<\/em>\uff1a<\/strong>int\u7c7b\u578b\u3002\u8f93\u51fa\u4e2a\u6570\u3002<\/li>\n<li><strong>feature<em>importances<\/em>\uff1a<\/strong>array\u7c7b\u578b\u3002\u7279\u5f81\u91cd\u8981\u5ea6\u3002<\/li>\n<li><strong>oob<em>score<\/em>\uff1a<\/strong>float\u7c7b\u578b\u3002\u7528\u888b\u5916\u6a21\u578b\u8bad\u7ec3\u6570\u636e\u7684\u5206\u6570\u3002<\/li>\n<li><strong>oob_decision<em>function<\/em>\uff1a<\/strong>array\u7c7b\u578b\u3002\u888b\u5916\u6a21\u578b\u8bad\u7ec3\u6570\u636e\u7684\u51b3\u7b56\u51fd\u6570\u3002<\/li>\n<\/ul>\n<h2>\u65b9\u6cd5<\/h2>\n<ul>\n<li><strong>apply(X[, check_input])\uff1a<\/strong>\u8fd4\u56de\u6bcf\u4e2a\u6837\u672c\u9884\u6d4b\u7684\u53f6\u5b50\u8282\u70b9\u7d22\u5f15\u3002<\/li>\n<li><strong>decision_path(X[, check_input])\uff1a<\/strong>\u8fd4\u56de\u6837\u672cX\u5728\u6811\u4e2d\u7684\u51b3\u7b56\u8def\u5f84\u3002<\/li>\n<li><strong>fit(X,y)\uff1a<\/strong>\u628a\u6570\u636e\u653e\u5165\u6a21\u578b\u4e2d\u8bad\u7ec3\u6a21\u578b\u3002<\/li>\n<li><strong>get_params([deep])\uff1a<\/strong>\u8fd4\u56de\u6a21\u578b\u7684\u53c2\u6570\uff0c\u53ef\u4ee5\u7528\u4e8ePipeline\u4e2d\u3002<\/li>\n<li><strong>predict(X)\uff1a<\/strong>\u9884\u6d4b\u6837\u672cX\u7684\u5206\u7c7b\u7c7b\u522b\u3002<\/li>\n<li><strong>predict_log_proba(X)\uff1a<\/strong>\u8fd4\u56de\u6837\u672cX\u5728\u5404\u4e2a\u7c7b\u522b\u4e0a\u5bf9\u5e94\u7684\u5bf9\u6570\u6982\u7387\u3002<\/li>\n<li><strong>predict_proba(X)\uff1a<\/strong>\u8fd4\u56de\u6837\u672cX\u5728\u5404\u4e2a\u7c7b\u522b\u4e0a\u5bf9\u5e94\u7684\u6982\u7387\u3002<\/li>\n<li><strong>score(X,y)\uff1a<\/strong>\u57fa\u4e8e\u62a5\u544a\u51b3\u5b9a\u7cfb\u6570$R^2$\u8bc4\u4f30\u6a21\u578b\u3002<\/li>\n<li><strong>set_prams(**params)\uff1a<\/strong>\u521b\u5efa\u6a21\u578b\u53c2\u6570\u3002<\/li>\n<\/ul>\n<h1>RandomForestRegressor<\/h1>\n<p>&emsp;&emsp;<code>RandomForestRegressor<\/code>\u6a21\u578b\u76f8\u6bd4\u8f83<code>RandomForestClassifier<\/code>\u6a21\u578b\u89e3\u51b3\u56de\u5f52\u95ee\u9898\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>scikit-learn\u5e93\u4e4b\u968f\u673a\u68ee\u6797 &emsp;&emsp;\u672c\u6587\u4e3b\u8981\u4ecb\u7ecd\u968f\u673a\u68ee\u6797\u7684\u4e24\u4e2a\u6a21\u578bRandomFor [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[276,298,293],"tags":[],"_links":{"self":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3182"}],"collection":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3182"}],"version-history":[{"count":0,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3182\/revisions"}],"wp:attachment":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3182"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3182"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3182"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}