{"categories":["python","\u6a5f\u68b0\u5b66\u7fd2","sklearn"],"provider_name":"Hatena Blog","author_url":"https://blog.hatena.ne.jp/hayataka2049/","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/h/hayataka2049/20190722/20190722062940.png","provider_url":"https://hatena.blog","type":"rich","url":"https://hayataka2049.hatenablog.jp/entry/2019/07/22/063232","published":"2019-07-22 06:32:32","author_name":"hayataka2049","blog_url":"https://hayataka2049.hatenablog.jp/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhayataka2049.hatenablog.jp%2Fentry%2F2019%2F07%2F22%2F063232\" title=\"\u3010python\u3011sklearn\u3067QuadraticDiscriminantAnalysis\uff08\u4e8c\u6b21\u5224\u5225\u5206\u6790\uff09\u3092\u8a66\u3059 - \u9759\u304b\u306a\u308b\u540d\u8f9e\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","width":"100%","height":"190","title":"\u3010python\u3011sklearn\u3067QuadraticDiscriminantAnalysis\uff08\u4e8c\u6b21\u5224\u5225\u5206\u6790\uff09\u3092\u8a66\u3059","blog_title":"\u9759\u304b\u306a\u308b\u540d\u8f9e","version":"1.0","description":"\u306f\u3058\u3081\u306b \u7dda\u5f62\u5224\u5225\u5206\u6790\u306f\u975e\u7dda\u5f62\u306a\u5206\u5e03\u306b\u5bfe\u5fdc\u3067\u304d\u306a\u3044\u306e\u3067\u3060\u3044\u305f\u3044\u30a4\u30de\u30a4\u30c1\u306a\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306b\u306a\u308b\u306e\u3067\u3059\u304c\u3001QDA\uff08\u4e8c\u6b21\u5224\u5225\u5206\u6790\uff09\u3060\u3068\u82e5\u5e72\u7de9\u548c\u3055\u308c\u307e\u3059\u3002 \u4e8c\u6b21\u5224\u5225\u5206\u6790\u306f\u305d\u306e\u540d\u306e\u901a\u308a\u5206\u96e2\u5883\u754c\u304c\u4e8c\u6b21\u95a2\u6570\u306b\u306a\u308a\u307e\u3059\u3002\u3068\u3044\u3046\u3053\u3068\u306f\u3001\u975e\u7dda\u5f62\u6027\u306f\u3042\u308a\u307e\u3059\u304c\u3001\u5927\u3057\u305f\u975e\u7dda\u5f62\u3067\u306f\u306a\u3044\u306e\u3067\u8907\u96d1\u306a\u5206\u5e03\u306b\u306f\u5bfe\u5fdc\u3067\u304d\u307e\u305b\u3093\u3002 \u307e\u3042\u3001\u4e00\u5fdc\u3084\u3063\u3066\u307f\u307e\u3059\u3002 \u5b9f\u9a13 \u4ee5\u4e0b\u306e\u3088\u3046\u306a\u30b3\u30fc\u30c9\u3067\u3001circles, moons, xor\u3092\u8a66\u3057\u3066\u307f\u307e\u3057\u305f\u3002\u4f8b\u306b\u3088\u3063\u3066\u3053\u306e\u8fba\u3092\u53c2\u8003\u306b\u3057\u3066\u3044\u307e\u3059\u3002Classifier comparison \u2014 scikit-learn 0.21.3 documentation import numpy as np im\u2026"}