{"id":3098,"date":"2022-02-27T11:29:15","date_gmt":"2022-02-27T03:29:15","guid":{"rendered":"https:\/\/egonlin.com\/?p=3098"},"modified":"2022-02-27T11:29:15","modified_gmt":"2022-02-27T03:29:15","slug":"%e7%ac%ac%e4%ba%8c%e8%8a%82%ef%bc%9a%e7%ba%bf%e6%80%a7%e6%94%af%e6%8c%81%e5%90%91%e9%87%8f%e6%9c%ba","status":"publish","type":"post","link":"https:\/\/egonlin.com\/?p=3098","title":{"rendered":"\u7b2c\u4e8c\u8282\uff1a\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a"},"content":{"rendered":"

\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a<\/h1>\n

  \u5728\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u4e2d\u8bf4\u5230\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u6709\u4e00\u4e2a\u7f3a\u70b9\u662f\u65e0\u6cd5\u5bf9\u5f02\u5e38\u70b9\u505a\u5904\u7406\uff0c\u4e5f\u6b63\u662f\u56e0\u4e3a\u8fd9\u4e9b\u5f02\u5e38\u70b9\u5bfc\u81f4\u6570\u636e\u53d8\u5f97\u7ebf\u6027\u4e0d\u53ef\u5206\u6216\u8005\u4f1a\u56e0\u4e3a\u5b83\u7684\u6b63\u597d\u88ab\u5224\u65ad\u4e3a\u652f\u6301\u5411\u91cf\u5bfc\u81f4\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u53d8\u5dee\u3002<\/p>\n

# \u5f02\u5e38\u70b9\u5bfc\u81f4\u6570\u636e\u7ebf\u6027\u4e0d\u53ef\u5206\u56fe\u4f8b\nimport matplotlib.pyplot as plt\nfrom matplotlib.font_manager import FontProperties\n%matplotlib inline\nfont = FontProperties(fname='\/Library\/Fonts\/Heiti.ttc')\n\nx1 = [2, 2.5, 3.2, 6.5]\nx11 = [1, 4.5, 5, 6]\nx2 = [1.2, 1.4, 1.5, 1.2]\nx22 = [1, 1.5, 1.3, 1]\n\nplt.scatter(x1, x2, s=50, color='b')\nplt.scatter(x11, x22, s=50, color='r')\nplt.vlines(3.9, 0.8, 2, colors="g", linestyles="-",\n           label='$w*x+b=0$', alpha=0.2)\nplt.text(1.1, 1.1, s='\u5f02\u5e38\u70b9A', fontsize=15, color='k',\n         ha='center', fontproperties=font)\nplt.text(6.3, 1.3, s='\u5f02\u5e38\u70b9B', fontsize=15, color='k',\n         ha='center', fontproperties=font)\nplt.legend()\nplt.show()<\/code><\/pre>\n
\"\"<\/div><\/p>\n
  \u4e0a\u56fe\u53ef\u4ee5\u770b\u51fa\u7531\u4e8e\u5f02\u5e38\u70b9A\u548c\u5f02\u5e38\u70b9B\u53ef\u80fd\u5bfc\u81f4\u65e0\u6cd5\u6309\u7167\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u5bf9\u4e0a\u8ff0\u6570\u636e\u96c6\u5206\u7c7b\u3002<\/p>\n
# \u5f02\u5e38\u70b9\u5bfc\u81f4\u6a21\u578b\u6cdb\u5316\u80fd\u529b\u53d8\u5dee\u56fe\u4f8b\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.font_manager import FontProperties\nfrom sklearn import svm\n%matplotlib inline\nfont = FontProperties(fname='\/Library\/Fonts\/Heiti.ttc')\n\nnp.random.seed(8)  # \u4fdd\u8bc1\u6570\u636e\u968f\u673a\u7684\u552f\u4e00\u6027\n\n# \u6784\u9020\u7ebf\u6027\u53ef\u5206\u6570\u636e\u70b9\narray = np.random.randn(20, 2)\nX = np.r_[array-[3, 3], array+[3, 3]]\ny = [0]*20+[1]*20\n\n# \u5efa\u7acbsvm\u6a21\u578b\nclf = svm.SVC(kernel='linear')\nclf.fit(X, y)\n\n# \u6784\u9020\u7b49\u7f51\u4e2a\u65b9\u9635\nx1_min, x1_max = X[:, 0].min(), X[:, 0].max(),\nx2_min, x2_max = X[:, 1].min(), X[:, 1].max(),\nx1, x2 = np.meshgrid(np.linspace(x1_min, x1_max),\n                     np.linspace(x2_min, x2_max))\n\n# \u5f97\u5230\u5411\u91cfw: w_0x_1+w_1x_2+b=0\nw = clf.coef_[0]\n# \u52a01\u540e\u624d\u53ef\u7ed8\u5236 -1 \u7684\u7b49\u9ad8\u7ebf [-1,0,1] + 1 = [0,1,2]\nf = w[0]*x1 + w[1]*x2 + clf.intercept_[0] + 1\n\n# \u7ed8\u5236H2\uff0c\u5373wx+b=-1\nplt.contour(x1, x2, f, [0], colors='k', linestyles='--', alpha=0.1)\nplt.text(2, -4, s='$H_2={\\omega}x+b=-1$', fontsize=10, color='r', ha='center')\n\n# \u7ed8\u5236\u5206\u9694\u8d85\u5e73\u9762\uff0c\u5373wx+b=0\nplt.contour(x1, x2, f, [1], colors='k', alpha=0.1)\nplt.text(2.5, -2, s='$\\omega{x}+b=0$', fontsize=10, color='r', ha='center')\nplt.text(2.5, -2.5, s='\u5206\u79bb\u8d85\u5e73\u9762', fontsize=10,\n         color='r', ha='center', fontproperties=font)\n\n# \u7ed8\u5236H1\uff0c\u5373wx+b=1\nplt.contour(x1, x2, f, [2], colors='k', linestyles='--')\nplt.text(3, 0, s='$H_1=\\omega{x}+b=1$', fontsize=10, color='r', ha='center')\n\n# \u7ed8\u5236\u6570\u636e\u6563\u70b9\u56fe\nplt.scatter(X[0:20, 0], X[0:20, 1], cmap=plt.cm.Paired, marker='x')\nplt.text(1, 1.8, s='\u652f\u6301\u5411\u91cf', fontsize=10, color='gray',\n         ha='center', fontproperties=font)\n\nplt.scatter(X[20:40, 0], X[20:40, 1], cmap=plt.cm.Paired, marker='o')\nplt.text(-1.5, -0.5, s='\u652f\u6301\u5411\u91cf', fontsize=10,\n         color='gray', ha='center', fontproperties=font)\n\n# \u7ed8\u5236\u5047\u8bbe\u7684\u5f02\u5e38\u70b9\u53ca\u5047\u8bbe\u7684\u95f4\u9694\u8fb9\u754c\uff0c**\u6beb\u65e0\u610f\u4e49\u7684\u4ee3\u7801**\uff0c\u4e3a\u4e86\u8bb2\u89e3\u7528\nplt.scatter(-1.5, 3, marker='x', c='b')\nplt.text(-1.5, 3.1, s='\u5f02\u5e38\u70b9A', fontsize=10,\n         color='r', ha='center', fontproperties=font)\nx_test = np.linspace(-3, 4, 666)\ny_test = -(w[0]+0.12)*x_test - (w[1]-0.002)*x_test+clf.intercept_[0]+1.8\ny_test_test = -(w[0]+0.12)*x_test - (w[1]-0.002)*x_test+clf.intercept_[0]+2.3\n\nplt.plot(x_test, y_test, linestyle='--')\nplt.plot(x_test, y_test_test)\n\nplt.xlim(x1_min-1, x1_max+1)\nplt.ylim(x2_min-1, x2_max+1)\nplt.show()<\/code><\/pre>\n
\"\"<\/div><\/p>\n
  \u4e0a\u56fe\u53ef\u4ee5\u770b\u51fa\u7531\u4e8e\u5f02\u5e38\u70b9\u5bfc\u81f4\u5206\u79bb\u8d85\u5e73\u9762\u4ece\u6de1\u5b9e\u7ebf\u53d8\u6210\u4e86\u9ec4\u8272\u7684\u90a3\u6761\u66f2\u7ebf\uff0c\u4ece\u56fe\u4e2d\u53ef\u4ee5\u660e\u663e\u770b\u51fa\u5f02\u5e38\u70b9\u4e25\u91cd\u5f71\u54cd\u4e86\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002<\/p>\n
  \u8fd9\u6b21\u8bb2\u5230\u7684\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a\uff08linear support vector machine\uff09\u5c06\u4fee\u6539\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u7684\u786c\u95f4\u9694\u6700\u5927\u5316\u4e3a\u8f6f\u95f4\u9694\u6700\u5927\u5316\u89e3\u51b3\u4e0a\u9762\u6709\u5f02\u5e38\u70b9\u5bfc\u81f4\u7684\u95ee\u9898\u3002<\/p>\n
\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a\u5b66\u4e60\u76ee\u6807<\/h1>\n
<\/p>
<\/div>
\u67e5\u770b\u66f4\u591a<\/h2>
\u8054\u7cfb\u7ba1\u7406\u5458\u5fae\u4fe1tutu19192010\uff0c\u6ce8\u518c\u8d26\u53f7<\/p>\n<\/div>
<\/div>
<\/td><\/tr>
<\/td><\/tr><\/tbody><\/table>
<\/td><\/tr><\/tbody><\/table><\/form>
Register<\/a><\/div>
Forgotten username or password?<\/a><\/div>
<\/div><\/div><\/div>
<\/div>","protected":false},"excerpt":{"rendered":"
\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a   \u5728\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u4e2d\u8bf4\u5230\u7ebf\u6027\u53ef\u5206\u652f\u6301\u5411\u91cf\u673a\u6709\u4e00\u4e2a\u7f3a\u70b9\u662f\u65e0\u6cd5\u5bf9\u5f02\u5e38\u70b9\u505a […]<\/p>\n","protected":false},"author":3,"featured_media":3094,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[276,291],"tags":[],"_links":{"self":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3098"}],"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=3098"}],"version-history":[{"count":0,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/posts\/3098\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=\/wp\/v2\/media\/3094"}],"wp:attachment":[{"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3098"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3098"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/egonlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3098"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}