{"id":478838,"date":"2023-08-09T09:39:01","date_gmt":"2023-08-09T09:39:01","guid":{"rendered":""},"modified":"2023-09-05T11:17:40","modified_gmt":"2023-09-05T11:17:40","slug":"scikit-learn","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/jp\/wiki\/scikit-learn\/","title":{"rendered":"\u30b5\u30a4\u30ad\u30c3\u30c8\u30e9\u30fc\u30f3"},"content":{"rendered":"<p>Scikit-learn (sklearn \u3068\u3082\u547c\u3070\u308c\u308b) \u306f\u3001Python \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u7528\u306e\u4eba\u6c17\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002\u30c7\u30fc\u30bf\u30de\u30a4\u30cb\u30f3\u30b0\u3001\u30c7\u30fc\u30bf\u5206\u6790\u3001\u6a5f\u68b0\u5b66\u7fd2\u30bf\u30b9\u30af\u7528\u306e\u30b7\u30f3\u30d7\u30eb\u3067\u52b9\u7387\u7684\u306a\u30c4\u30fc\u30eb\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002Scikit-learn \u306f\u30e6\u30fc\u30b6\u30fc\u30d5\u30ec\u30f3\u30c9\u30ea\u30fc\u306b\u8a2d\u8a08\u3055\u308c\u3066\u304a\u308a\u3001\u521d\u5fc3\u8005\u306b\u3082\u7d4c\u9a13\u8c4a\u5bcc\u306a\u6a5f\u68b0\u5b66\u7fd2\u5b9f\u8df5\u8005\u306b\u3082\u7406\u60f3\u7684\u306a\u9078\u629e\u80a2\u3067\u3059\u3002\u30e6\u30fc\u30b6\u30fc\u304c\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u52b9\u679c\u7684\u306b\u69cb\u7bc9\u304a\u3088\u3073\u5c55\u958b\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u5e45\u5e83\u3044\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3001\u30c4\u30fc\u30eb\u3001\u30e6\u30fc\u30c6\u30a3\u30ea\u30c6\u30a3\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/p>\n<h2>Scikit-learn \u306e\u8d77\u6e90\u306e\u6b74\u53f2<\/h2>\n<p>Scikit-learn \u306f\u30012007 \u5e74\u306b Google Summer of Code \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u4e00\u74b0\u3068\u3057\u3066 David Cournapeau \u306b\u3088\u3063\u3066\u6700\u521d\u306b\u958b\u767a\u3055\u308c\u307e\u3057\u305f\u3002\u3053\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u76ee\u7684\u306f\u3001\u958b\u767a\u8005\u3001\u7814\u7a76\u8005\u3001\u5b9f\u8df5\u8005\u304c\u5229\u7528\u3067\u304d\u308b\u3001\u30e6\u30fc\u30b6\u30fc\u30d5\u30ec\u30f3\u30c9\u30ea\u30fc\u306a\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u63d0\u4f9b\u3059\u308b\u3053\u3068\u3067\u3057\u305f\u3002\u3053\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u9577\u5e74\u306b\u308f\u305f\u3063\u3066\u4eba\u6c17\u304c\u9ad8\u307e\u308a\u3001\u6a5f\u68b0\u5b66\u7fd2\u306e Python \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u57fa\u790e\u3068\u306a\u308a\u307e\u3057\u305f\u3002<\/p>\n<h2>Scikit-learn\u306e\u8a73\u7d30\u60c5\u5831<\/h2>\n<p>Scikit-learn \u306f\u3001\u5206\u985e\u3001\u56de\u5e30\u3001\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3001\u6b21\u5143\u524a\u6e1b\u306a\u3069\u3001\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u591a\u69d8\u306a\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u5e83\u7bc4\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3068\u308f\u304b\u308a\u3084\u3059\u3044 API \u8a2d\u8a08\u306b\u3088\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u52b9\u679c\u7684\u306b\u7406\u89e3\u3057\u3066\u5b9f\u88c5\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u3001NumPy\u3001SciPy\u3001Matplotlib \u306a\u3069\u306e\u4ed6\u306e\u4e00\u822c\u7684\u306a Python \u30d1\u30c3\u30b1\u30fc\u30b8\u4e0a\u306b\u69cb\u7bc9\u3055\u308c\u3066\u304a\u308a\u3001\u305d\u306e\u6a5f\u80fd\u3068\u3001\u3088\u308a\u5e83\u7bc4\u306a\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30b9 \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3068\u306e\u7d71\u5408\u3092\u5f37\u5316\u3057\u307e\u3059\u3002<\/p>\n<h2>Scikit-learn\u306e\u5185\u90e8\u69cb\u9020<\/h2>\n<p>Scikit-learn \u306f\u30e2\u30b8\u30e5\u30fc\u30eb\u8a2d\u8a08\u3092\u63a1\u7528\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u958b\u767a\u8005\u306f\u8eca\u8f2a\u306e\u518d\u767a\u660e\u3092\u3059\u308b\u3053\u3068\u306a\u304f\u3001\u6a5f\u68b0\u5b66\u7fd2\u306e\u7279\u5b9a\u306e\u5074\u9762\u306b\u96c6\u4e2d\u3067\u304d\u307e\u3059\u3002\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u3055\u307e\u3056\u307e\u306a\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4e2d\u5fc3\u306b\u69cb\u6210\u3055\u308c\u3066\u304a\u308a\u3001\u305d\u308c\u305e\u308c\u304c\u7279\u5b9a\u306e\u6a5f\u68b0\u5b66\u7fd2\u30bf\u30b9\u30af\u5c02\u7528\u3067\u3059\u3002\u4e3b\u306a\u30e2\u30b8\u30e5\u30fc\u30eb\u306b\u306f\u6b21\u306e\u3082\u306e\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<ul>\n<li><strong>\u524d\u51e6\u7406<\/strong>: \u7279\u5fb4\u306e\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u3001\u6b63\u898f\u5316\u3001\u88dc\u5b8c\u306a\u3069\u306e\u30c7\u30fc\u30bf\u524d\u51e6\u7406\u30bf\u30b9\u30af\u3092\u51e6\u7406\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u6559\u5e2b\u3042\u308a\u5b66\u7fd2<\/strong>: \u5206\u985e\u3001\u56de\u5e30\u3001\u30b5\u30dd\u30fc\u30c8 \u30d9\u30af\u30bf\u30fc \u30de\u30b7\u30f3\u306a\u3069\u306e\u6559\u5e2b\u3042\u308a\u30bf\u30b9\u30af\u7528\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u6559\u5e2b\u306a\u3057\u5b66\u7fd2<\/strong>: \u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3001\u6b21\u5143\u524a\u6e1b\u3001\u7570\u5e38\u691c\u51fa\u306e\u305f\u3081\u306e\u30c4\u30fc\u30eb\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u30e2\u30c7\u30eb\u306e\u9078\u629e\u3068\u8a55\u4fa1<\/strong>: \u30e2\u30c7\u30eb\u9078\u629e\u3001\u30cf\u30a4\u30d1\u30fc\u30d1\u30e9\u30e1\u30fc\u30bf\u8abf\u6574\u3001\u30af\u30ed\u30b9\u691c\u8a3c\u3092\u4f7f\u7528\u3057\u305f\u30e2\u30c7\u30eb\u8a55\u4fa1\u306e\u305f\u3081\u306e\u30e6\u30fc\u30c6\u30a3\u30ea\u30c6\u30a3\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002<\/li>\n<\/ul>\n<h2>Scikit-learn \u306e\u4e3b\u8981\u6a5f\u80fd\u306e\u5206\u6790<\/h2>\n<p>Scikit-learn \u306e\u4eba\u6c17\u306f\u3001\u305d\u306e\u4e3b\u306a\u6a5f\u80fd\u304b\u3089\u751f\u307e\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n<ul>\n<li><strong>\u4f7f\u3044\u3084\u3059\u3044<\/strong>: Scikit-learn \u306e\u4e00\u8cab\u3057\u305f API \u3068\u6574\u7406\u3055\u308c\u305f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u3088\u308a\u3001\u3055\u307e\u3056\u307e\u306a\u30ec\u30d9\u30eb\u306e\u5c02\u9580\u77e5\u8b58\u3092\u6301\u3064\u30e6\u30fc\u30b6\u30fc\u304c\u5229\u7528\u3067\u304d\u307e\u3059\u3002<\/li>\n<li><strong>\u5e45\u5e83\u3044\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u9078\u629e<\/strong>: \u3055\u307e\u3056\u307e\u306a\u6a5f\u68b0\u5b66\u7fd2\u30bf\u30b9\u30af\u3084\u30b7\u30ca\u30ea\u30aa\u306b\u5bfe\u5fdc\u3059\u308b\u5e45\u5e83\u3044\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u3068\u30b5\u30dd\u30fc\u30c8<\/strong>: \u6d3b\u767a\u306a\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u304c\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u6210\u9577\u306b\u8ca2\u732e\u3057\u3001\u5b9a\u671f\u7684\u306a\u66f4\u65b0\u3068\u30d0\u30b0\u4fee\u6b63\u3092\u4fdd\u8a3c\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u7d71\u5408<\/strong>: Scikit-learn \u306f\u4ed6\u306e Python \u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u7d71\u5408\u3055\u308c\u3001\u30a8\u30f3\u30c9\u30c4\u30fc\u30a8\u30f3\u30c9\u306e\u30c7\u30fc\u30bf\u5206\u6790\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u5b9f\u73fe\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u52b9\u7387<\/strong>: \u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u304c\u6700\u9069\u5316\u3055\u308c\u3066\u304a\u308a\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u52b9\u7387\u7684\u306b\u51e6\u7406\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u6559\u80b2<\/strong>: \u30e6\u30fc\u30b6\u30fc\u30d5\u30ec\u30f3\u30c9\u30ea\u30fc\u306a\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u306f\u3001\u6a5f\u68b0\u5b66\u7fd2\u306e\u6982\u5ff5\u306e\u6307\u5c0e\u3068\u5b66\u7fd2\u306b\u7279\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/li>\n<\/ul>\n<h2>Scikit-learn \u306e\u7a2e\u985e\u3068\u305d\u306e\u7528\u9014<\/h2>\n<p>Scikit-learn \u306f\u3001\u305d\u308c\u305e\u308c\u7279\u5b9a\u306e\u76ee\u7684\u3092\u679c\u305f\u3059\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/p>\n<ul>\n<li><strong>\u5206\u985e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/strong>: \u30b9\u30d1\u30e0\u691c\u51fa\u3084\u753b\u50cf\u5206\u985e\u306a\u3069\u306e\u30ab\u30c6\u30b4\u30ea\u7d50\u679c\u3092\u4e88\u6e2c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/li>\n<li><strong>\u56de\u5e30\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/strong>: \u4f4f\u5b85\u4fa1\u683c\u3084\u682a\u4fa1\u306a\u3069\u306e\u9023\u7d9a\u7684\u306a\u6570\u5024\u3092\u4e88\u6e2c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/li>\n<li><strong>\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/strong>: \u985e\u4f3c\u5ea6\u306e\u5c3a\u5ea6\u306b\u57fa\u3065\u3044\u3066\u985e\u4f3c\u306e\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/li>\n<li><strong>\u6b21\u5143\u524a\u6e1b\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/strong>: \u91cd\u8981\u306a\u60c5\u5831\u3092\u4fdd\u6301\u3057\u306a\u304c\u3089\u6a5f\u80fd\u306e\u6570\u3092\u6e1b\u3089\u3059\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/li>\n<li><strong>\u30e2\u30c7\u30eb\u9078\u629e\u304a\u3088\u3073\u8a55\u4fa1\u30c4\u30fc\u30eb<\/strong>: \u6700\u9069\u306a\u30e2\u30c7\u30eb\u306e\u9078\u629e\u3068\u305d\u306e\u30cf\u30a4\u30d1\u30fc\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8abf\u6574\u3092\u652f\u63f4\u3057\u307e\u3059\u3002<\/li>\n<\/ul>\n<table>\n<thead>\n<tr>\n<th>\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u7a2e\u985e<\/th>\n<th>\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u4f8b<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u5206\u985e<\/td>\n<td>\u6c7a\u5b9a\u6728\u3001\u30e9\u30f3\u30c0\u30e0\u30d5\u30a9\u30ec\u30b9\u30c8<\/td>\n<\/tr>\n<tr>\n<td>\u56de\u5e30<\/td>\n<td>\u7dda\u5f62\u56de\u5e30\u3001\u30ea\u30c3\u30b8\u56de\u5e30<\/td>\n<\/tr>\n<tr>\n<td>\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0<\/td>\n<td>K\u5e73\u5747\u6cd5\u3001DBSCAN<\/td>\n<\/tr>\n<tr>\n<td>\u6b21\u5143\u524a\u6e1b<\/td>\n<td>\u4e3b\u6210\u5206\u5206\u6790 (PCA)<\/td>\n<\/tr>\n<tr>\n<td>\u30e2\u30c7\u30eb\u306e\u9078\u629e\u3068\u8a55\u4fa1<\/td>\n<td>\u30b0\u30ea\u30c3\u30c9\u30b5\u30fc\u30c1CV\u3001\u30af\u30ed\u30b9\u5024\u30b9\u30b3\u30a2<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Scikit-learn \u306e\u4f7f\u3044\u65b9\u3001\u554f\u984c\u70b9\u3001\u89e3\u6c7a\u7b56<\/h2>\n<p>Scikit-learn \u306f\u3055\u307e\u3056\u307e\u306a\u65b9\u6cd5\u3067\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/p>\n<ol>\n<li><strong>\u30c7\u30fc\u30bf\u306e\u6e96\u5099<\/strong>: \u524d\u51e6\u7406\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u307f\u3001\u524d\u51e6\u7406\u3057\u3001\u5909\u63db\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u30e2\u30c7\u30eb\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0<\/strong>\u9069\u5207\u306a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u9078\u629e\u3057\u3001\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u3001\u30cf\u30a4\u30d1\u30fc\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u5fae\u8abf\u6574\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u30e2\u30c7\u30eb\u306e\u8a55\u4fa1<\/strong>: \u30e1\u30c8\u30ea\u30c3\u30af\u3068\u30af\u30ed\u30b9\u691c\u8a3c\u624b\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u30e2\u30c7\u30eb\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u8a55\u4fa1\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u5c0e\u5165<\/strong>: \u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u6e08\u307f\u306e\u30e2\u30c7\u30eb\u3092\u5b9f\u969b\u306e\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u5411\u3051\u306e\u904b\u7528\u30b7\u30b9\u30c6\u30e0\u306b\u7d71\u5408\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n<p>\u4e00\u822c\u7684\u306a\u554f\u984c\u3068\u89e3\u6c7a\u7b56\u306b\u306f\u3001\u4e0d\u5747\u8861\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u51e6\u7406\u3001\u95a2\u9023\u3059\u308b\u6a5f\u80fd\u306e\u9078\u629e\u3001\u6b63\u898f\u5316\u624b\u6cd5\u306b\u3088\u308b\u904e\u5270\u9069\u5408\u306e\u89e3\u6c7a\u306a\u3069\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<h2>\u4e3b\u306a\u7279\u5fb4\u3068\u985e\u4f3c\u7528\u8a9e\u3068\u306e\u6bd4\u8f03<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u5074\u9762<\/th>\n<th>\u30b5\u30a4\u30ad\u30c3\u30c8\u30e9\u30fc\u30f3<\/th>\n<th>\u30c6\u30f3\u30bd\u30eb\u30d5\u30ed\u30fc<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u96c6\u4e2d<\/td>\n<td>\u4e00\u822c\u7684\u306a\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d6\u30e9\u30ea<\/td>\n<td>\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af<\/td>\n<\/tr>\n<tr>\n<td>\u4f7f\u3044\u3084\u3059\u3055<\/td>\n<td>\u30e6\u30fc\u30b6\u30fc\u30d5\u30ec\u30f3\u30c9\u30ea\u30fc\u3067\u30b7\u30f3\u30d7\u30eb\u306aAPI<\/td>\n<td>\u3088\u308a\u8907\u96d1\u3001\u7279\u306bTensorFlow<\/td>\n<\/tr>\n<tr>\n<td>\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u591a\u69d8\u6027<\/td>\n<td>\u5305\u62ec\u7684\u3067\u591a\u69d8\u306a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/td>\n<td>\u4e3b\u306b\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u7126\u70b9\u3092\u5f53\u3066\u308b<\/td>\n<\/tr>\n<tr>\n<td>\u5b66\u7fd2\u66f2\u7dda<\/td>\n<td>\u521d\u5fc3\u8005\u3067\u3082\u7c21\u5358\u306b\u5b66\u7fd2\u3067\u304d\u308b<\/td>\n<td>\u6025\u5cfb\u306a\u5b66\u7fd2\u66f2\u7dda<\/td>\n<\/tr>\n<tr>\n<td>\u4f7f\u7528\u4f8b<\/td>\n<td>\u591a\u69d8\u306a\u6a5f\u68b0\u5b66\u7fd2\u30bf\u30b9\u30af<\/td>\n<td>\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3001\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Scikit-learn \u306b\u95a2\u9023\u3059\u308b\u5c55\u671b\u3068\u5c06\u6765\u306e\u6280\u8853<\/h2>\n<p>Scikit-learn \u306e\u5c06\u6765\u306b\u306f\u3001\u6b21\u306e\u3088\u3046\u306a\u523a\u6fc0\u7684\u306a\u53ef\u80fd\u6027\u304c\u79d8\u3081\u3089\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n<ol>\n<li><strong>\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3068\u306e\u7d71\u5408<\/strong>: \u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0 \u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u306e\u9023\u643a\u306b\u3088\u308a\u3001\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9 \u30e2\u30c7\u30eb\u306e\u30b7\u30fc\u30e0\u30ec\u30b9\u306a\u7d71\u5408\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/li>\n<li><strong>\u9ad8\u5ea6\u306a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/strong>: \u6700\u5148\u7aef\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u7d44\u307f\u8fbc\u3093\u3067\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u5411\u4e0a\u3057\u307e\u3059\u3002<\/li>\n<li><strong>\u81ea\u52d5\u6a5f\u68b0\u5b66\u7fd2 (AutoML)<\/strong>: \u81ea\u52d5\u30e2\u30c7\u30eb\u9078\u629e\u3068\u30cf\u30a4\u30d1\u30fc\u30d1\u30e9\u30e1\u30fc\u30bf\u8abf\u6574\u306e\u305f\u3081\u306e AutoML \u6a5f\u80fd\u306e\u7d71\u5408\u3002<\/li>\n<\/ol>\n<h2>\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u3092 Scikit-learn \u3067\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u307e\u305f\u306f Scikit-learn \u3068\u95a2\u9023\u4ed8\u3051\u308b\u65b9\u6cd5<\/h2>\n<p>\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001Scikit-learn \u306e\u6a5f\u80fd\u3092\u5f37\u5316\u3059\u308b\u4e0a\u3067\u5f79\u5272\u3092\u679c\u305f\u3057\u307e\u3059\u3002<\/p>\n<ol>\n<li><strong>\u30c7\u30fc\u30bf\u53ce\u96c6<\/strong>\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u3092\u63a1\u7528\u3059\u308b\u3068\u3001\u3055\u307e\u3056\u307e\u306a\u5730\u7406\u7684\u5730\u57df\u304b\u3089\u30c7\u30fc\u30bf\u3092\u53ce\u96c6\u3057\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0 \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u5145\u5b9f\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/li>\n<li><strong>\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u3068\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3<\/strong>: \u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001\u30c7\u30fc\u30bf\u53ce\u96c6\u304a\u3088\u3073\u30e2\u30c7\u30eb\u306e\u5c55\u958b\u4e2d\u306b\u6a5f\u5bc6\u30c7\u30fc\u30bf\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u3092\u78ba\u4fdd\u3067\u304d\u307e\u3059\u3002<\/li>\n<li><strong>\u5206\u6563\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/strong>: \u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001\u6a5f\u68b0\u5b66\u7fd2\u30bf\u30b9\u30af\u3092\u8907\u6570\u306e\u30b5\u30fc\u30d0\u30fc\u306b\u5206\u6563\u3057\u3001\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3092\u5411\u4e0a\u3055\u305b\u308b\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/li>\n<\/ol>\n<h2>\u95a2\u9023\u30ea\u30f3\u30af<\/h2>\n<p>Scikit-learn \u306e\u8a73\u7d30\u306b\u3064\u3044\u3066\u306f\u3001\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3084\u305d\u306e\u4ed6\u306e\u8cb4\u91cd\u306a\u30ea\u30bd\u30fc\u30b9\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<ul>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/documentation.html\" target=\"_new\" rel=\"noopener nofollow\">Scikit-learn \u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/scikit-learn\/scikit-learn\" target=\"_new\" rel=\"noopener nofollow\">GitHub \u30ea\u30dd\u30b8\u30c8\u30ea<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/tutorial\/index.html\" target=\"_new\" rel=\"noopener nofollow\">Scikit-learn \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/auto_examples\/index.html\" target=\"_new\" rel=\"noopener nofollow\">Scikit-learn \u306e\u4f8b<\/a><\/li>\n<\/ul>\n<p>\u7d50\u8ad6\u3068\u3057\u3066\u3001Scikit-learn \u306f\u6a5f\u68b0\u5b66\u7fd2\u306e\u5206\u91ce\u306b\u304a\u3051\u308b\u57fa\u790e\u3068\u3057\u3066\u4f4d\u7f6e\u3065\u3051\u3089\u308c\u3066\u304a\u308a\u3001\u521d\u5fc3\u8005\u3068\u719f\u7df4\u8005\u306e\u4e21\u65b9\u306b\u8c4a\u5bcc\u306a\u30c4\u30fc\u30eb\u30dc\u30c3\u30af\u30b9\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u305d\u306e\u4f7f\u3044\u3084\u3059\u3055\u3001\u6c4e\u7528\u6027\u3001\u305d\u3057\u3066\u6d3b\u767a\u306a\u30b3\u30df\u30e5\u30cb\u30c6\u30a3 \u30b5\u30dd\u30fc\u30c8\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u5206\u91ce\u3067\u306e\u57fa\u672c\u7684\u306a\u30c4\u30fc\u30eb\u3068\u3057\u3066\u306e\u5730\u4f4d\u304c\u78ba\u7acb\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u306e\u9032\u6b69\u306b\u4f34\u3044\u3001Scikit-learn \u306f\u9032\u5316\u3092\u7d9a\u3051\u3001\u6a5f\u68b0\u5b66\u7fd2\u611b\u597d\u5bb6\u306b\u3068\u3063\u3066\u3055\u3089\u306b\u5f37\u529b\u3067\u30a2\u30af\u30bb\u30b9\u3057\u3084\u3059\u3044\u672a\u6765\u3092\u7d04\u675f\u3057\u3066\u3044\u307e\u3059\u3002<\/p>","protected":false},"featured_media":470421,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478838","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Scikit-learn: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is Scikit-learn?","answer":"<p>Scikit-learn, often referred to as sklearn, is a widely-used open-source machine learning library designed for Python. It provides a range of tools and algorithms for various machine learning tasks, making it a popular choice for both beginners and experts.<\/p>"},{"question":"Who developed Scikit-learn and when?","answer":"<p>Scikit-learn was initially developed by David Cournapeau in 2007 as part of the Google Summer of Code project. Since then, it has grown in popularity and has become an integral part of the Python machine learning ecosystem.<\/p>"},{"question":"What types of machine learning algorithms does Scikit-learn offer?","answer":"<p>Scikit-learn offers a diverse set of algorithms including classification, regression, clustering, and dimensionality reduction. It also provides tools for model selection, evaluation, and preprocessing of data.<\/p>"},{"question":"What are the key features of Scikit-learn?","answer":"<p>Scikit-learn is known for its ease of use, extensive documentation, and well-organized API. It offers a wide range of algorithms, integrates seamlessly with other Python libraries, and is optimized for performance. Additionally, it serves well for educational purposes.<\/p>"},{"question":"How does Scikit-learn compare to deep learning frameworks like TensorFlow and PyTorch?","answer":"<p>Scikit-learn is a general machine learning library suitable for various tasks. In contrast, TensorFlow and PyTorch are deep learning frameworks primarily focused on neural networks. Scikit-learn has a gentler learning curve for beginners, whereas deep learning frameworks may require more expertise.<\/p>"},{"question":"How can proxy servers be used with Scikit-learn?","answer":"<p>Proxy servers can enhance Scikit-learn in several ways. They can aid in data collection from different regions, ensure data privacy and security during collection and deployment, and facilitate distributed computing for improved scalability.<\/p>"},{"question":"What are the future prospects of Scikit-learn?","answer":"<p>The future of Scikit-learn looks promising. It may integrate with deep learning libraries, incorporate advanced algorithms, and even include automated machine learning (AutoML) capabilities for streamlined model selection and tuning.<\/p>"},{"question":"Where can I find more information about Scikit-learn?","answer":"<p>For more details, you can explore the <a href=\"https:\/\/scikit-learn.org\/stable\/documentation.html\" target=\"_new\">official Scikit-learn documentation<\/a>, check out the <a href=\"https:\/\/github.com\/scikit-learn\/scikit-learn\" target=\"_new\">GitHub repository<\/a>, or delve into <a href=\"https:\/\/scikit-learn.org\/stable\/tutorial\/index.html\" target=\"_new\">tutorials<\/a> and <a href=\"https:\/\/scikit-learn.org\/stable\/auto_examples\/index.html\" target=\"_new\">examples<\/a>.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki\/478838","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki\/478838\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/media\/470421"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/media?parent=478838"}],"curies":[{"name":"\u3046\u30fc\u3093","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}