{"id":476784,"date":"2023-08-09T07:36:15","date_gmt":"2023-08-09T07:36:15","guid":{"rendered":""},"modified":"2023-09-05T11:13:26","modified_gmt":"2023-09-05T11:13:26","slug":"delta-rule","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/cn\/wiki\/delta-rule\/","title":{"rendered":"\u5fb7\u5c14\u5854\u89c4\u5219"},"content":{"rendered":"<p>Delta \u89c4\u5219\uff0c\u4e5f\u79f0\u4e3a Widrow-Hoff \u89c4\u5219\u6216\u6700\u5c0f\u5747\u65b9 (LMS) \u89c4\u5219\uff0c\u662f\u673a\u5668\u5b66\u4e60\u548c\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4e2d\u7684\u57fa\u672c\u6982\u5ff5\u3002\u5b83\u662f\u4e00\u79cd\u589e\u91cf\u5b66\u4e60\u7b97\u6cd5\uff0c\u7528\u4e8e\u8c03\u6574\u4eba\u5de5\u795e\u7ecf\u5143\u4e4b\u95f4\u7684\u8fde\u63a5\u6743\u91cd\uff0c\u4f7f\u7f51\u7edc\u80fd\u591f\u6839\u636e\u8f93\u5165\u6570\u636e\u5b66\u4e60\u5e76\u8c03\u6574\u5176\u54cd\u5e94\u3002 Delta\u89c4\u5219\u5728\u57fa\u4e8e\u68af\u5ea6\u4e0b\u964d\u7684\u4f18\u5316\u7b97\u6cd5\u4e2d\u8d77\u7740\u81f3\u5173\u91cd\u8981\u7684\u4f5c\u7528\uff0c\u5e76\u5e7f\u6cdb\u5e94\u7528\u4e8e\u5404\u4e2a\u9886\u57df\uff0c\u5305\u62ec\u6a21\u5f0f\u8bc6\u522b\u3001\u4fe1\u53f7\u5904\u7406\u548c\u63a7\u5236\u7cfb\u7edf\u3002<\/p>\n<h2>\u4e09\u89d2\u6d32\u7edf\u6cbb\u7684\u8d77\u6e90\u5386\u53f2\u53ca\u5176\u9996\u6b21\u63d0\u53ca<\/h2>\n<p>Delta \u89c4\u5219\u7531 Bernard Widrow \u548c Marcian Hoff \u4e8e 1960 \u5e74\u9996\u6b21\u63d0\u51fa\uff0c\u4f5c\u4e3a\u4ed6\u4eec\u81ea\u9002\u5e94\u7cfb\u7edf\u7814\u7a76\u7684\u4e00\u90e8\u5206\u3002\u4ed6\u4eec\u7684\u76ee\u6807\u662f\u5f00\u53d1\u4e00\u79cd\u673a\u5236\uff0c\u4f7f\u7f51\u7edc\u80fd\u591f\u4ece\u793a\u4f8b\u4e2d\u5b66\u4e60\u5e76\u81ea\u6211\u8c03\u6574\u5176\u7a81\u89e6\u6743\u91cd\uff0c\u4ee5\u6700\u5927\u9650\u5ea6\u5730\u51cf\u5c11\u5176\u8f93\u51fa\u4e0e\u6240\u9700\u8f93\u51fa\u4e4b\u95f4\u7684\u8bef\u5dee\u3002\u4ed6\u4eec\u7684\u5f00\u521b\u6027\u8bba\u6587\u300a\u81ea\u9002\u5e94\u5f00\u5173\u7535\u8def\u300b\u6807\u5fd7\u7740 Delta \u89c4\u5219\u7684\u8bde\u751f\uff0c\u5e76\u4e3a\u795e\u7ecf\u7f51\u7edc\u5b66\u4e60\u7b97\u6cd5\u9886\u57df\u5960\u5b9a\u4e86\u57fa\u7840\u3002<\/p>\n<h2>\u6709\u5173 Delta \u89c4\u5219\u7684\u8be6\u7ec6\u4fe1\u606f\uff1a\u5c55\u5f00\u4e3b\u9898 Delta \u89c4\u5219<\/h2>\n<p>Delta \u89c4\u5219\u57fa\u4e8e\u76d1\u7763\u5b66\u4e60\u7684\u539f\u7406\u8fd0\u884c\uff0c\u5176\u4e2d\u7f51\u7edc\u4f7f\u7528\u8f93\u5165\u8f93\u51fa\u6570\u636e\u5bf9\u8fdb\u884c\u8bad\u7ec3\u3002\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u7f51\u7edc\u5c06\u5176\u9884\u6d4b\u8f93\u51fa\u4e0e\u671f\u671b\u8f93\u51fa\u8fdb\u884c\u6bd4\u8f83\uff0c\u8ba1\u7b97\u8bef\u5dee\uff08\u4e5f\u79f0\u4e3a\u589e\u91cf\uff09\uff0c\u5e76\u76f8\u5e94\u5730\u66f4\u65b0\u8fde\u63a5\u6743\u91cd\u3002\u5173\u952e\u76ee\u6807\u662f\u6700\u5c0f\u5316\u591a\u6b21\u8fed\u4ee3\u7684\u8bef\u5dee\uff0c\u76f4\u5230\u7f51\u7edc\u6536\u655b\u5230\u5408\u9002\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<h2>Delta \u89c4\u5219\u7684\u5185\u90e8\u7ed3\u6784\uff1aDelta \u89c4\u5219\u5982\u4f55\u8fd0\u4f5c<\/h2>\n<p>Delta\u89c4\u5219\u7684\u5de5\u4f5c\u673a\u5236\u53ef\u4ee5\u6982\u62ec\u4e3a\u4ee5\u4e0b\u6b65\u9aa4\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u521d\u59cb\u5316<\/strong>\uff1a\u7528\u5c0f\u7684\u968f\u673a\u503c\u6216\u9884\u5b9a\u503c\u521d\u59cb\u5316\u795e\u7ecf\u5143\u4e4b\u95f4\u7684\u8fde\u63a5\u6743\u91cd\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u524d\u5411\u4f20\u64ad<\/strong>\uff1a\u5411\u7f51\u7edc\u63d0\u4f9b\u8f93\u5165\u6a21\u5f0f\uff0c\u5e76\u5c06\u5176\u5411\u524d\u4f20\u64ad\u901a\u8fc7\u795e\u7ecf\u5143\u5c42\u4ee5\u751f\u6210\u8f93\u51fa\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u8bef\u5dee\u8ba1\u7b97<\/strong>\uff1a\u5c06\u7f51\u7edc\u7684\u8f93\u51fa\u4e0e\u671f\u671b\u7684\u8f93\u51fa\u8fdb\u884c\u6bd4\u8f83\uff0c\u5e76\u8ba1\u7b97\u5b83\u4eec\u4e4b\u95f4\u7684\u8bef\u5dee\uff08delta\uff09\u3002\u8bef\u5dee\u901a\u5e38\u8868\u793a\u4e3a\u9884\u6d4b\u8f93\u51fa\u4e0e\u76ee\u6807\u8f93\u51fa\u4e4b\u95f4\u7684\u5dee\u5f02\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u91cd\u91cf\u66f4\u65b0<\/strong>\uff1a\u6839\u636e\u8ba1\u7b97\u51fa\u7684\u8bef\u5dee\u8c03\u6574\u8fde\u63a5\u7684\u6743\u91cd\u3002\u6743\u91cd\u66f4\u65b0\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a<\/p>\n<p>\u0394W = \u5b66\u4e60\u7387 * \u589e\u91cf * \u8f93\u5165<\/p>\n<p>\u8fd9\u91cc\uff0c\u0394W\u662f\u6743\u91cd\u66f4\u65b0\uff0clearning_rate\u662f\u4e00\u4e2a\u5c0f\u7684\u6b63\u5e38\u6570\uff0c\u79f0\u4e3a\u5b66\u4e60\u7387\uff08\u6216\u6b65\u957f\uff09\uff0cinput\u8868\u793a\u8f93\u5165\u6a21\u5f0f\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u91cd\u590d<\/strong>\uff1a\u7ee7\u7eed\u5448\u73b0\u8f93\u5165\u6a21\u5f0f\u3001\u8ba1\u7b97\u8bef\u5dee\u5e76\u66f4\u65b0\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u6bcf\u4e2a\u6a21\u5f0f\u7684\u6743\u91cd\u3002\u8fed\u4ee3\u6b64\u8fc7\u7a0b\uff0c\u76f4\u5230\u7f51\u7edc\u8fbe\u5230\u4ee4\u4eba\u6ee1\u610f\u7684\u7cbe\u5ea6\u6c34\u5e73\u6216\u6536\u655b\u5230\u7a33\u5b9a\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<\/li>\n<\/ol>\n<h2>Delta\u89c4\u5219\u7684\u5173\u952e\u7279\u5f81\u5206\u6790<\/h2>\n<p>Delta \u89c4\u5219\u5177\u6709\u51e0\u4e2a\u5173\u952e\u7279\u6027\uff0c\u4f7f\u5176\u6210\u4e3a\u5404\u79cd\u5e94\u7528\u7684\u70ed\u95e8\u9009\u62e9\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u5728\u7ebf\u5b66\u4e60<\/strong>\uff1aDelta \u89c4\u5219\u662f\u4e00\u79cd\u5728\u7ebf\u5b66\u4e60\u7b97\u6cd5\uff0c\u8fd9\u610f\u5473\u7740\u5b83\u4f1a\u5728\u6bcf\u6b21\u5448\u73b0\u8f93\u5165\u6a21\u5f0f\u540e\u66f4\u65b0\u6743\u91cd\u3002\u6b64\u529f\u80fd\u4f7f\u7f51\u7edc\u80fd\u591f\u5feb\u901f\u9002\u5e94\u4e0d\u65ad\u53d8\u5316\u7684\u6570\u636e\uff0c\u5e76\u4f7f\u5176\u9002\u5408\u5b9e\u65f6\u5e94\u7528\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u9002\u5e94\u6027<\/strong>\uff1aDelta \u89c4\u5219\u53ef\u4ee5\u9002\u5e94\u8f93\u5165\u6570\u636e\u7684\u7edf\u8ba1\u5c5e\u6027\u53ef\u80fd\u968f\u65f6\u95f4\u53d8\u5316\u7684\u975e\u5e73\u7a33\u73af\u5883\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u7b80\u5355<\/strong>\uff1a\u8be5\u7b97\u6cd5\u7684\u7b80\u5355\u6027\u4f7f\u5176\u6613\u4e8e\u5b9e\u73b0\u4e14\u8ba1\u7b97\u6548\u7387\u9ad8\uff0c\u7279\u522b\u662f\u5bf9\u4e8e\u4e2d\u5c0f\u578b\u795e\u7ecf\u7f51\u7edc\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u5c40\u90e8\u4f18\u5316<\/strong>\uff1a\u6743\u91cd\u66f4\u65b0\u662f\u6839\u636e\u5404\u4e2a\u6a21\u5f0f\u7684\u8bef\u5dee\u6267\u884c\u7684\uff0c\u4f7f\u5176\u6210\u4e3a\u5c40\u90e8\u4f18\u5316\u7684\u4e00\u79cd\u5f62\u5f0f\u3002<\/p>\n<\/li>\n<\/ol>\n<h2>Delta\u89c4\u5219\u7684\u7c7b\u578b\uff1a\u4f7f\u7528\u8868\u683c\u548c\u5217\u8868\u6765\u7f16\u5199<\/h2>\n<p>\u6839\u636e\u5177\u4f53\u7684\u5b66\u4e60\u4efb\u52a1\u548c\u7f51\u7edc\u67b6\u6784\uff0cDelta \u89c4\u5219\u6709\u4e0d\u540c\u7684\u53d8\u4f53\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u503c\u5f97\u6ce8\u610f\u7684\u7c7b\u578b\uff1a<\/p>\n<table>\n<thead>\n<tr>\n<th>\u7c7b\u578b<\/th>\n<th>\u63cf\u8ff0<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u6279\u91cf\u589e\u91cf\u89c4\u5219<\/td>\n<td>\u7d2f\u79ef\u8bef\u5dee\u540e\u8ba1\u7b97\u6743\u91cd\u66f4\u65b0<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u591a\u79cd\u8f93\u5165\u6a21\u5f0f\u3002\u5bf9\u4e8e\u79bb\u7ebf\u5b66\u4e60\u5f88\u6709\u7528\u3002<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<tr>\n<td>\u9012\u5f52\u589e\u91cf<\/td>\n<td>\u9012\u5f52\u5e94\u7528\u66f4\u65b0\u4ee5\u9002\u5e94\u987a\u5e8f<\/td>\n<\/tr>\n<tr>\n<td>\u89c4\u5219<\/td>\n<td>\u8f93\u5165\u6a21\u5f0f\uff0c\u4f8b\u5982\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3002<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<tr>\n<td>\u6b63\u5219\u5316Delta<\/td>\n<td>\u7eb3\u5165\u6b63\u5219\u5316\u9879\u4ee5\u9632\u6b62\u8fc7\u5ea6\u62df\u5408<\/td>\n<\/tr>\n<tr>\n<td>\u89c4\u5219<\/td>\n<td>\u5e76\u63d0\u9ad8\u6cdb\u5316\u80fd\u529b\u3002<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<tr>\n<td>Delta-Bar-Delta<\/td>\n<td>\u6839\u636e\u9519\u8bef\u7684\u7b26\u53f7\u8c03\u6574\u5b66\u4e60\u7387<\/td>\n<\/tr>\n<tr>\n<td>\u89c4\u5219<\/td>\n<td>\u4ee5\u53ca\u4e4b\u524d\u7684\u66f4\u65b0\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Delta\u89c4\u5219\u7684\u4f7f\u7528\u65b9\u6cd5\u3001\u4f7f\u7528\u8fc7\u7a0b\u4e2d\u9047\u5230\u7684\u95ee\u9898\u53ca\u89e3\u51b3\u65b9\u6cd5<\/h2>\n<p>Delta \u89c4\u5219\u9002\u7528\u4e8e\u5404\u4e2a\u9886\u57df\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u6a21\u5f0f\u8bc6\u522b<\/strong>\uff1aDelta \u89c4\u5219\u5e7f\u6cdb\u7528\u4e8e\u6a21\u5f0f\u8bc6\u522b\u4efb\u52a1\uff0c\u4f8b\u5982\u56fe\u50cf\u548c\u8bed\u97f3\u8bc6\u522b\uff0c\u5176\u4e2d\u7f51\u7edc\u5b66\u4e60\u5c06\u8f93\u5165\u6a21\u5f0f\u4e0e\u76f8\u5e94\u7684\u6807\u7b7e\u5173\u8054\u8d77\u6765\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u63a7\u5236\u7cfb\u7edf<\/strong>\uff1a\u5728\u63a7\u5236\u7cfb\u7edf\u4e2d\uff0cDelta \u89c4\u5219\u7528\u4e8e\u6839\u636e\u53cd\u9988\u8c03\u6574\u63a7\u5236\u53c2\u6570\uff0c\u4ee5\u5b9e\u73b0\u6240\u9700\u7684\u7cfb\u7edf\u884c\u4e3a\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u4fe1\u53f7\u5904\u7406<\/strong>\uff1aDelta \u89c4\u5219\u7528\u4e8e\u81ea\u9002\u5e94\u4fe1\u53f7\u5904\u7406\u5e94\u7528\uff0c\u4f8b\u5982\u566a\u58f0\u6d88\u9664\u548c\u56de\u58f0\u6291\u5236\u3002<\/p>\n<\/li>\n<\/ol>\n<p>\u5c3d\u7ba1 Delta \u89c4\u5219\u5f88\u6709\u7528\uff0c\u4f46\u5b83\u4e5f\u5b58\u5728\u4e00\u4e9b\u6311\u6218\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u6536\u655b\u901f\u5ea6<\/strong>\uff1a\u7b97\u6cd5\u53ef\u80fd\u6536\u655b\u7f13\u6162\uff0c\u5c24\u5176\u662f\u5728\u9ad8\u7ef4\u7a7a\u95f4\u6216\u590d\u6742\u7f51\u7edc\u4e2d\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u5c40\u90e8\u6781\u5c0f\u503c<\/strong>\uff1aDelta \u89c4\u5219\u53ef\u80fd\u4f1a\u9677\u5165\u5c40\u90e8\u6700\u5c0f\u503c\uff0c\u65e0\u6cd5\u627e\u5230\u5168\u5c40\u6700\u4f18\u503c\u3002<\/p>\n<\/li>\n<\/ol>\n<p>\u4e3a\u4e86\u89e3\u51b3\u8fd9\u4e9b\u95ee\u9898\uff0c\u7814\u7a76\u4eba\u5458\u5f00\u53d1\u4e86\u4ee5\u4e0b\u6280\u672f\uff1a<\/p>\n<ul>\n<li>\n<p><strong>\u5b66\u4e60\u7387\u8c03\u5ea6<\/strong>\uff1a\u8bad\u7ec3\u65f6\u52a8\u6001\u8c03\u6574\u5b66\u4e60\u7387\uff0c\u5e73\u8861\u6536\u655b\u901f\u5ea6\u548c\u7a33\u5b9a\u6027\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u52bf\u5934<\/strong>\uff1a\u5728\u6743\u91cd\u66f4\u65b0\u4e2d\u7eb3\u5165\u52a8\u91cf\u9879\uff0c\u4ee5\u9003\u907f\u5c40\u90e8\u6781\u5c0f\u503c\u5e76\u52a0\u901f\u6536\u655b\u3002<\/p>\n<\/li>\n<\/ul>\n<h2>\u4e3b\u8981\u7279\u5f81\u53ca\u4e0e\u7c7b\u4f3c\u672f\u8bed\u7684\u5176\u4ed6\u6bd4\u8f83\uff1a\u4ee5\u8868\u683c\u548c\u5217\u8868\u7684\u5f62\u5f0f<\/h2>\n<table>\n<thead>\n<tr>\n<th>Delta\u89c4\u5219\u5bf9\u6bd4<\/th>\n<th>\u63cf\u8ff0<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u53cd\u5411\u4f20\u64ad<\/td>\n<td>\u4e24\u8005\u90fd\u662f\u795e\u7ecf\u7f51\u7edc\u7684\u76d1\u7763\u5b66\u4e60\u7b97\u6cd5<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u7f51\u7edc\uff0c\u4f46\u53cd\u5411\u4f20\u64ad\u4f7f\u7528\u57fa\u4e8e\u94fe\u89c4\u5219\u7684<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u6743\u91cd\u66f4\u65b0\u65b9\u6cd5\uff0c\u800c Delta \u89c4\u5219\u5219\u4f7f\u7528<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u5b9e\u9645\u8f93\u51fa\u4e0e\u671f\u671b\u8f93\u51fa\u4e4b\u95f4\u7684\u8bef\u5dee\u3002<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<tr>\n<td>\u611f\u77e5\u5668\u89c4\u5219<\/td>\n<td>\u611f\u77e5\u5668\u89c4\u5219\u662f\u4e00\u79cd\u4e8c\u5143\u5206\u7c7b\u7b97\u6cd5<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u57fa\u4e8e\u8f93\u51fa\u7684\u7b26\u53f7\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0cDelta \u89c4\u5219<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u9002\u7528\u4e8e\u8fde\u7eed\u8f93\u51fa\u548c\u56de\u5f52\u4efb\u52a1\u3002<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<tr>\n<td>\u6700\u5c0f\u4e8c\u4e58\u6cd5<\/td>\n<td>\u4e24\u8005\u90fd\u7528\u4e8e\u7ebf\u6027\u56de\u5f52\u95ee\u9898\uff0c\u4f46\u662f<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u6700\u5c0f\u4e8c\u4e58\u6cd5\u6700\u5c0f\u5316\u8bef\u5dee\u5e73\u65b9\u548c\uff0c<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\u800cDelta\u89c4\u5219\u4f7f\u7528\u77ac\u65f6\u8bef\u5dee\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u4e0e Delta \u89c4\u5219\u76f8\u5173\u7684\u672a\u6765\u524d\u666f\u548c\u6280\u672f<\/h2>\n<p>Delta \u89c4\u5219\u4e3a\u66f4\u5148\u8fdb\u7684\u5b66\u4e60\u7b97\u6cd5\u548c\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u94fa\u5e73\u4e86\u9053\u8def\u3002\u968f\u7740\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u4e0d\u65ad\u53d1\u5c55\uff0c\u7814\u7a76\u4eba\u5458\u6b63\u5728\u63a2\u7d22\u5404\u79cd\u65b9\u5411\u6765\u589e\u5f3a\u5b66\u4e60\u7b97\u6cd5\u7684\u6027\u80fd\u548c\u6548\u7387\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u6df1\u5ea6\u5b66\u4e60<\/strong>\uff1a\u5c06 Delta \u89c4\u5219\u4e0e\u6df1\u5ea6\u5b66\u4e60\u67b6\u6784\u76f8\u7ed3\u5408\uff0c\u53ef\u4ee5\u8fdb\u884c\u5206\u5c42\u8868\u793a\u5b66\u4e60\uff0c\u4f7f\u7f51\u7edc\u80fd\u591f\u5904\u7406\u66f4\u590d\u6742\u7684\u4efb\u52a1\u548c\u5927\u6570\u636e\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u5f3a\u5316\u5b66\u4e60<\/strong>\uff1a\u5c06 Delta \u89c4\u5219\u4e0e\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\u76f8\u7ed3\u5408\u53ef\u4ee5\u4ea7\u751f\u66f4\u6709\u6548\u3001\u9002\u5e94\u6027\u66f4\u5f3a\u7684\u5b66\u4e60\u7cfb\u7edf\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u5143\u5b66\u4e60<\/strong>\uff1a\u5143\u5b66\u4e60\u6280\u672f\u65e8\u5728\u6539\u8fdb\u5b66\u4e60\u8fc7\u7a0b\u672c\u8eab\uff0c\u4f7f Delta \u89c4\u5219\u7b49\u7b97\u6cd5\u66f4\u52a0\u9ad8\u6548\u5e76\u4e14\u80fd\u591f\u8de8\u4efb\u52a1\u6cdb\u5316\u3002<\/p>\n<\/li>\n<\/ol>\n<h2>\u5982\u4f55\u4f7f\u7528\u4ee3\u7406\u670d\u52a1\u5668\u6216\u5c06\u5176\u4e0e Delta \u89c4\u5219\u5173\u8054<\/h2>\n<p>\u4ee3\u7406\u670d\u52a1\u5668\u5728\u6570\u636e\u6536\u96c6\u548c\u9884\u5904\u7406\u4e2d\u53d1\u6325\u7740\u81f3\u5173\u91cd\u8981\u7684\u4f5c\u7528\uff0c\u8fd9\u662f\u8bad\u7ec3 Delta \u57fa\u4e8e\u89c4\u5219\u7684\u7f51\u7edc\u7b49\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u4ee5\u4e0b\u662f\u4ee3\u7406\u670d\u52a1\u5668\u4e0e Delta \u89c4\u5219\u5173\u8054\u7684\u4e00\u4e9b\u65b9\u6cd5\uff1a<\/p>\n<ol>\n<li>\n<p><strong>\u6570\u636e\u91c7\u96c6<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u7528\u4e8e\u6536\u96c6\u548c\u533f\u540d\u5316\u6765\u81ea\u5404\u79cd\u6765\u6e90\u7684\u6570\u636e\uff0c\u6709\u52a9\u4e8e\u83b7\u53d6\u4e0d\u540c\u7684\u6570\u636e\u96c6\u8fdb\u884c\u8bad\u7ec3\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u8d1f\u8f7d\u5747\u8861<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u5c06\u8bf7\u6c42\u5206\u53d1\u5230\u591a\u4e2a\u8d44\u6e90\uff0c\u4f18\u5316\u4e86Delta\u89c4\u5219\u5728\u7ebf\u5b66\u4e60\u6a21\u5f0f\u7684\u6570\u636e\u83b7\u53d6\u6d41\u7a0b\u3002<\/p>\n<\/li>\n<li>\n<p><strong>\u9690\u79c1\u548c\u5b89\u5168<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u5728\u6570\u636e\u4f20\u8f93\u8fc7\u7a0b\u4e2d\u4fdd\u62a4\u654f\u611f\u6570\u636e\uff0c\u786e\u4fddDelta\u89c4\u5219\u8bad\u7ec3\u4e2d\u4f7f\u7528\u7684\u4fe1\u606f\u7684\u673a\u5bc6\u6027\u3002<\/p>\n<\/li>\n<\/ol>\n<h2>\u76f8\u5173\u94fe\u63a5<\/h2>\n<p>\u6709\u5173 Delta \u89c4\u5219\u53ca\u76f8\u5173\u4e3b\u9898\u7684\u66f4\u591a\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605\u4ee5\u4e0b\u8d44\u6e90\uff1a<\/p>\n<ol>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/document\/1113663\" target=\"_new\" rel=\"noopener nofollow\">\u81ea\u9002\u5e94\u5f00\u5173\u7535\u8def - \u539f\u59cb\u8bba\u6587<\/a><\/li>\n<li><a href=\"https:\/\/www.cs.cornell.edu\/courses\/cs4780\/2018fa\/lectures\/lecturenote07.html\" target=\"_new\" rel=\"noopener nofollow\">Delta \u89c4\u5219\u7b80\u4ecb \u2013 \u5eb7\u5948\u5c14\u5927\u5b66<\/a><\/li>\n<li><a href=\"https:\/\/www.geeksforgeeks.org\/machine-learning-delta-rule-and-perceptron-rule\/\" target=\"_new\" rel=\"noopener nofollow\">\u673a\u5668\u5b66\u4e60\uff1aDelta \u89c4\u5219\u548c\u611f\u77e5\u5668\u89c4\u5219 \u2013 GeeksforGeeks<\/a><\/li>\n<\/ol>\n<p>\u603b\u4e4b\uff0cDelta \u89c4\u5219\u662f\u4e00\u79cd\u57fa\u7840\u7b97\u6cd5\uff0c\u5bf9\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u548c\u673a\u5668\u5b66\u4e60\u7684\u53d1\u5c55\u505a\u51fa\u4e86\u91cd\u5927\u8d21\u732e\u3002\u5b83\u9002\u5e94\u4e0d\u65ad\u53d8\u5316\u7684\u73af\u5883\u548c\u6267\u884c\u589e\u91cf\u66f4\u65b0\u7684\u80fd\u529b\u4f7f\u5176\u6210\u4e3a\u5404\u79cd\u5e94\u7528\u7a0b\u5e8f\u7684\u5b9d\u8d35\u5de5\u5177\u3002\u968f\u7740\u6280\u672f\u7684\u8fdb\u6b65\uff0cDelta \u89c4\u5219\u53ef\u80fd\u4f1a\u7ee7\u7eed\u6fc0\u53d1\u65b0\u7684\u5b66\u4e60\u7b97\u6cd5\u5e76\u4fc3\u8fdb\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u8fdb\u6b65\u3002<\/p>","protected":false},"featured_media":476785,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476784","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Delta Rule: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is the Delta rule?","answer":"<p>The Delta rule, also known as the Widrow-Hoff rule or the Least Mean Square (LMS) rule, is a fundamental concept in machine learning and neural networks. It is an incremental learning algorithm that adjusts the weights of connections between artificial neurons based on input data, enabling the network to learn and adapt its responses.<\/p>"},{"question":"Who introduced the Delta rule?","answer":"<p>The Delta rule was first introduced by Bernard Widrow and Marcian Hoff in 1960 as part of their research on adaptive systems. Their groundbreaking paper titled \"Adaptive Switching Circuits\" marked the birth of the Delta rule and laid the foundation for neural network learning algorithms.<\/p>"},{"question":"How does the Delta rule work?","answer":"<p>The Delta rule operates on supervised learning principles. During training, the network compares its predicted output with the desired output, calculates the error (delta), and updates the connection weights accordingly. The process is repeated for each input pattern until the network converges to a suitable solution.<\/p>"},{"question":"What are the key features of the Delta rule?","answer":"<p>The Delta rule exhibits features like online learning, adaptability to non-stationary environments, simplicity in implementation, and local optimization for weight updates.<\/p>"},{"question":"What are the types of Delta rule?","answer":"<p>There are several types of Delta rule variations, including Batch Delta Rule, Recursive Delta Rule, Regularized Delta Rule, and Delta-Bar-Delta Rule. Each type serves specific learning tasks and network architectures.<\/p>"},{"question":"Where is the Delta rule used?","answer":"<p>The Delta rule finds application in various fields, including pattern recognition, control systems, and signal processing. It is used to solve problems where the network needs to learn from data and adapt to changing conditions.<\/p>"},{"question":"What are the challenges with the Delta rule?","answer":"<p>Some challenges with the Delta rule include convergence speed, potential for getting stuck in local minima, and the need for careful tuning of hyperparameters like the learning rate.<\/p>"},{"question":"How can proxy servers be associated with the Delta rule?","answer":"<p>Proxy servers play a role in data collection and preprocessing, providing a way to gather diverse datasets for training, optimize data acquisition, and ensure data privacy and security during the training process.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/476784","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/476784\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media\/476785"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media?parent=476784"}],"curies":[{"name":"\u53ef\u6e7f\u6027\u7c89\u5242","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}