{"id":3161,"date":"2022-02-27T12:40:17","date_gmt":"2022-02-27T04:40:17","guid":{"rendered":"https:\/\/egonlin.com\/?p=3161"},"modified":"2022-02-27T12:41:18","modified_gmt":"2022-02-27T04:41:18","slug":"%e7%ac%ac%e5%9b%9b%e7%af%87%ef%bc%9a%e6%a2%af%e5%ba%a6%e6%8f%90%e5%8d%87%e7%ae%97%e6%b3%95%e4%bb%a3%e7%a0%81%e9%b8%a2%e5%b0%be%e8%8a%b1%e5%88%86%e7%b1%bb%e4%ba%a4%e5%8f%89%e9%aa%8c%e8%af%81","status":"publish","type":"post","link":"https:\/\/egonlin.com\/?p=3161","title":{"rendered":"\u7b2c\u56db\u7bc7\uff1a\u68af\u5ea6\u63d0\u5347\u7b97\u6cd5\u4ee3\u7801(\u9e22\u5c3e\u82b1\u5206\u7c7b)+\u4ea4\u53c9\u9a8c\u8bc1\u8c03\u53c2"},"content":{"rendered":"

\u68af\u5ea6\u63d0\u5347\u7b97\u6cd5\u4ee3\u7801(\u9e22\u5c3e\u82b1\u5206\u7c7b)+\u4ea4\u53c9\u9a8c\u8bc1\u8c03\u53c2<\/h1>\n

\u5bfc\u5165\u6a21\u5757<\/h1>\n
import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import ListedColormap\nfrom matplotlib.font_manager import FontProperties\nfrom sklearn.datasets import load_iris\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn import metrics\nfrom sklearn.model_selection import GridSearchCV\n%matplotlib inline\nfont = FontProperties(fname='\/Library\/Fonts\/Heiti.ttc')<\/code><\/pre>\n
\u5bfc\u5165\u6570\u636e<\/h1>\n
iris_data = load_iris()\nX = iris_data.data[0:100, [2, 3]]\ny = iris_data.target[0:100]\nlabel_list = ['\u5c71\u9e22\u5c3e', '\u6742\u8272\u9e22\u5c3e']<\/code><\/pre>\n
\u6784\u9020\u51b3\u7b56\u8fb9\u754c<\/h1>\n
def plot_decision_regions(X, y, classifier=None):\n    marker_list = ['o', 'x', 's']\n    color_list = ['r', 'b', 'g']\n    cmap = ListedColormap(color_list[:len(np.unique(y))])\n\n    x1_min, x1_max = X[:, 0].min()-1, X[:, 0].max()+1\n    x2_min, x2_max = X[:, 1].min()-1, X[:, 1].max()+1\n    t1 = np.linspace(x1_min, x1_max, 666)\n    t2 = np.linspace(x2_min, x2_max, 666)\n\n    x1, x2 = np.meshgrid(t1, t2)\n    y_hat = classifier.predict(np.array([x1.ravel(), x2.ravel()]).T)\n    y_hat = y_hat.reshape(x1.shape)\n    plt.contourf(x1, x2, y_hat, alpha=0.2, cmap=cmap)\n    plt.xlim(x1_min, x1_max)\n    plt.ylim(x2_min, x2_max)\n\n    for ind, clas in enumerate(np.unique(y)):\n        plt.scatter(X[y == clas, 0], X[y == clas, 1], alpha=0.8, s=50,\n                    c=color_list[ind], marker=marker_list[ind], label=label_list[clas])<\/code><\/pre>\n
\u8bad\u7ec3\u6a21\u578b<\/h1>\n
gbc = GradientBoostingClassifier(random_state=1)\ngbc.fit(X, y)\ny_pred = gbc.predict(X)\ny_predprob = gbc.predict_proba(X)[:, 1]\nprint("\u7cbe\u51c6\u5ea6:{:.4f}".format(metrics.accuracy_score(y, y_pred)))\nprint("AUC\u5206\u6570(\u8bad\u7ec3\u96c6):{:.4f}".format(metrics.roc_auc_score(y, y_predprob)))<\/code><\/pre>\n
\u7cbe\u51c6\u5ea6:1.0000\nAUC\u5206\u6570(\u8bad\u7ec3\u96c6):1.0000<\/code><\/pre>\n
\u53ef\u89c6\u5316<\/h2>\n
plot_decision_regions(X, y, classifier=gbc)\nplt.xlabel('\u82b1\u74e3\u957f\u5ea6\uff08cm\uff09', fontproperties=font)\nplt.ylabel('\u82b1\u74e3\u5bbd\u5ea6\uff08cm\uff09', fontproperties=font)\nplt.title('\u68af\u5ea6\u63d0\u5347\u6cd5\u7b97\u6cd5\u4ee3\u7801(\u9e22\u5c3e\u82b1\u5206\u7c7b)',\n          fontproperties=font, fontsize=20)\nplt.legend(prop=font)\nplt.show()<\/code><\/pre>\n
\"\"<\/div><\/p>\n
\u4ea4\u53c9\u9a8c\u8bc1\u8bad\u7ec3\u6a21\u578b<\/h1>\n
\u627e\u5230\u5408\u9002n_estimators<\/h2>\n
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\u67e5\u770b\u66f4\u591a<\/h2>
\u8054\u7cfb\u7ba1\u7406\u5458\u5fae\u4fe1tutu19192010\uff0c\u6ce8\u518c\u8d26\u53f7<\/p>\n<\/div>
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\u68af\u5ea6\u63d0\u5347\u7b97\u6cd5\u4ee3\u7801(\u9e22\u5c3e\u82b1\u5206\u7c7b)+\u4ea4\u53c9\u9a8c\u8bc1\u8c03\u53c2 \u5bfc\u5165\u6a21\u5757 import numpy as np import m […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[296,293],"tags":[],"_links":{"self":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3161"}],"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=3161"}],"version-history":[{"count":0,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3161\/revisions"}],"wp:attachment":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3161"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3161"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}