{"id":478675,"date":"2023-08-09T09:36:47","date_gmt":"2023-08-09T09:36:47","guid":{"rendered":""},"modified":"2023-09-05T11:17:20","modified_gmt":"2023-09-05T11:17:20","slug":"regularization-l1-l2","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/regularization-l1-l2\/","title":{"rendered":"Ch\u00ednh quy h\u00f3a (L1, L2)"},"content":{"rendered":"<h2>Gi\u1edbi thi\u1ec7u<\/h2>\n<p>Trong l\u0129nh v\u1ef1c h\u1ecdc m\u00e1y v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u, Ch\u00ednh quy h\u00f3a (L1, L2) l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt n\u1ec1n t\u1ea3ng \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 gi\u1ea3m thi\u1ec3u nh\u1eefng th\u00e1ch th\u1ee9c do trang b\u1ecb qu\u00e1 m\u1ee9c v\u00e0 \u0111\u1ed9 ph\u1ee9c t\u1ea1p c\u1ee7a m\u00f4 h\u00ecnh \u0111\u1eb7t ra. C\u00e1c ph\u01b0\u01a1ng ph\u00e1p ch\u00ednh quy h\u00f3a, c\u1ee5 th\u1ec3 l\u00e0 ch\u00ednh quy h\u00f3a L1 (Lasso) v\u00e0 L2 (Ridge), \u0111\u00e3 t\u00ecm th\u1ea5y v\u1ecb tr\u00ed c\u1ee7a m\u00ecnh kh\u00f4ng ch\u1ec9 trong l\u0129nh v\u1ef1c khoa h\u1ecdc d\u1eef li\u1ec7u m\u00e0 c\u00f2n trong vi\u1ec7c t\u1ed1i \u01b0u h\u00f3a hi\u1ec7u su\u1ea5t c\u1ee7a c\u00e1c c\u00f4ng ngh\u1ec7 \u0111a d\u1ea1ng, bao g\u1ed3m c\u1ea3 m\u00e1y ch\u1ee7 proxy. Trong b\u00e0i vi\u1ebft to\u00e0n di\u1ec7n n\u00e0y, ch\u00fang t\u00f4i \u0111i s\u00e2u v\u00e0o Ch\u00ednh quy h\u00f3a (L1, L2), kh\u00e1m ph\u00e1 l\u1ecbch s\u1eed, c\u01a1 ch\u1ebf, lo\u1ea1i, \u1ee9ng d\u1ee5ng v\u00e0 ti\u1ec1m n\u0103ng trong t\u01b0\u01a1ng lai c\u1ee7a n\u00f3, \u0111\u1eb7c bi\u1ec7t t\u1eadp trung v\u00e0o m\u1ed1i li\u00ean h\u1ec7 c\u1ee7a n\u00f3 v\u1edbi vi\u1ec7c cung c\u1ea5p m\u00e1y ch\u1ee7 proxy.<\/p>\n<h2>Ngu\u1ed3n g\u1ed1c v\u00e0 \u0111\u1ec1 c\u1eadp s\u1edbm<\/h2>\n<p>Kh\u00e1i ni\u1ec7m Ch\u00ednh quy h\u00f3a n\u1ed5i l\u00ean nh\u01b0 m\u1ed9t ph\u1ea3n \u1ee9ng \u0111\u1ed1i v\u1edbi hi\u1ec7n t\u01b0\u1ee3ng trang b\u1ecb qu\u00e1 m\u1ee9c trong c\u00e1c m\u00f4 h\u00ecnh h\u1ecdc m\u00e1y, \u0111\u1ec1 c\u1eadp \u0111\u1ebfn c\u00e1c tr\u01b0\u1eddng h\u1ee3p khi m\u1ed9t m\u00f4 h\u00ecnh tr\u1edf n\u00ean qu\u00e1 ph\u00f9 h\u1ee3p v\u1edbi d\u1eef li\u1ec7u hu\u1ea5n luy\u1ec7n v\u00e0 g\u1eb7p kh\u00f3 kh\u0103n trong vi\u1ec7c kh\u00e1i qu\u00e1t h\u00f3a t\u1ed1t d\u1eef li\u1ec7u m\u1edbi, ch\u01b0a \u0111\u01b0\u1ee3c nh\u00ecn th\u1ea5y. Thu\u1eadt ng\u1eef \u201cch\u00ednh quy h\u00f3a\u201d \u0111\u01b0\u1ee3c \u0111\u1eb7t ra \u0111\u1ec3 m\u00f4 t\u1ea3 vi\u1ec7c \u0111\u01b0a ra c\u00e1c r\u00e0ng bu\u1ed9c ho\u1eb7c h\u00ecnh ph\u1ea1t \u0111\u1ed1i v\u1edbi c\u00e1c tham s\u1ed1 c\u1ee7a m\u00f4 h\u00ecnh trong qu\u00e1 tr\u00ecnh \u0111\u00e0o t\u1ea1o, ki\u1ec3m so\u00e1t hi\u1ec7u qu\u1ea3 \u0111\u1ed9 l\u1edbn c\u1ee7a ch\u00fang v\u00e0 ng\u0103n ch\u1eb7n c\u00e1c gi\u00e1 tr\u1ecb c\u1ef1c \u0111oan.<\/p>\n<p>Nh\u1eefng \u00fd t\u01b0\u1edfng n\u1ec1n t\u1ea3ng v\u1ec1 Ch\u00ednh quy h\u00f3a ban \u0111\u1ea7u \u0111\u01b0\u1ee3c Norbert Wiener h\u00ecnh th\u00e0nh v\u00e0o nh\u1eefng n\u0103m 1930, nh\u01b0ng ph\u1ea3i \u0111\u1ebfn cu\u1ed1i th\u1ebf k\u1ef7 20, nh\u1eefng kh\u00e1i ni\u1ec7m n\u00e0y m\u1edbi thu h\u00fat \u0111\u01b0\u1ee3c s\u1ef1 ch\u00fa \u00fd trong h\u1ecdc m\u00e1y v\u00e0 th\u1ed1ng k\u00ea. S\u1ef1 ra \u0111\u1eddi c\u1ee7a d\u1eef li\u1ec7u nhi\u1ec1u chi\u1ec1u v\u00e0 c\u00e1c m\u00f4 h\u00ecnh ng\u00e0y c\u00e0ng ph\u1ee9c t\u1ea1p \u0111\u00e3 l\u00e0m n\u1ed5i b\u1eadt s\u1ef1 c\u1ea7n thi\u1ebft c\u1ee7a c\u00e1c k\u1ef9 thu\u1eadt m\u1ea1nh m\u1ebd \u0111\u1ec3 duy tr\u00ec t\u00ednh kh\u00e1i qu\u00e1t h\u00f3a m\u00f4 h\u00ecnh. Ch\u00ednh quy h\u00f3a L1 v\u00e0 L2, hai h\u00ecnh th\u1ee9c Ch\u00ednh quy h\u00f3a n\u1ed5i b\u1eadt, \u0111\u00e3 \u0111\u01b0\u1ee3c gi\u1edbi thi\u1ec7u v\u00e0 ch\u00ednh th\u1ee9c h\u00f3a nh\u01b0 c\u00e1c k\u1ef9 thu\u1eadt \u0111\u1ec3 gi\u1ea3i quy\u1ebft nh\u1eefng th\u00e1ch th\u1ee9c n\u00e0y.<\/p>\n<h2>Ra m\u1eaft ch\u00ednh quy h\u00f3a (L1, L2)<\/h2>\n<h3>C\u01a1 h\u1ecdc v\u00e0 v\u1eadn h\u00e0nh<\/h3>\n<p>C\u00e1c ph\u01b0\u01a1ng ph\u00e1p ch\u00ednh quy h\u00f3a ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch th\u00eam c\u00e1c s\u1ed1 h\u1ea1ng ph\u1ea1t v\u00e0o h\u00e0m m\u1ea5t m\u00e1t trong qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n. Nh\u1eefng h\u00ecnh ph\u1ea1t n\u00e0y kh\u00f4ng khuy\u1ebfn kh\u00edch m\u00f4 h\u00ecnh g\u00e1n tr\u1ecdng s\u1ed1 qu\u00e1 l\u1edbn cho m\u1ed9t s\u1ed1 t\u00ednh n\u0103ng nh\u1ea5t \u0111\u1ecbnh, do \u0111\u00f3 ng\u0103n m\u00f4 h\u00ecnh nh\u1ea5n m\u1ea1nh qu\u00e1 m\u1ee9c c\u00e1c t\u00ednh n\u0103ng \u1ed3n \u00e0o ho\u1eb7c kh\u00f4ng li\u00ean quan c\u00f3 th\u1ec3 d\u1eabn \u0111\u1ebfn t\u00ecnh tr\u1ea1ng trang b\u1ecb qu\u00e1 m\u1ee9c. S\u1ef1 kh\u00e1c bi\u1ec7t ch\u00ednh gi\u1eefa ch\u00ednh quy h\u00f3a L1 v\u00e0 L2 n\u1eb1m \u1edf lo\u1ea1i h\u00ecnh ph\u1ea1t m\u00e0 ch\u00fang \u00e1p d\u1ee5ng.<\/p>\n<p><strong>Ch\u00ednh quy h\u00f3a L1 (Lasso):<\/strong> Ch\u00ednh quy h\u00f3a L1 \u0111\u01b0a ra m\u1ed9t thu\u1eadt ng\u1eef ph\u1ea1t t\u1ef7 l\u1ec7 thu\u1eadn v\u1edbi gi\u00e1 tr\u1ecb tuy\u1ec7t \u0111\u1ed1i c\u1ee7a c\u00e1c tr\u1ecdng s\u1ed1 tham s\u1ed1 c\u1ee7a m\u00f4 h\u00ecnh. \u0110i\u1ec1u n\u00e0y c\u00f3 t\u00e1c d\u1ee5ng \u0111\u1ea9y m\u1ed9t s\u1ed1 tr\u1ecdng s\u1ed1 tham s\u1ed1 v\u1ec1 ch\u00ednh x\u00e1c b\u1eb1ng 0, th\u1ef1c hi\u1ec7n hi\u1ec7u qu\u1ea3 vi\u1ec7c l\u1ef1a ch\u1ecdn t\u00ednh n\u0103ng v\u00e0 d\u1eabn \u0111\u1ebfn m\u1ed9t m\u00f4 h\u00ecnh th\u01b0a th\u1edbt h\u01a1n.<\/p>\n<p><strong>Ch\u00ednh quy h\u00f3a L2 (S\u01b0\u1eddn):<\/strong> M\u1eb7t kh\u00e1c, ch\u00ednh quy h\u00f3a L2 th\u00eam m\u1ed9t s\u1ed1 h\u1ea1ng ph\u1ea1t t\u1ef7 l\u1ec7 v\u1edbi b\u00ecnh ph\u01b0\u01a1ng c\u1ee7a c\u00e1c tr\u1ecdng s\u1ed1 tham s\u1ed1. \u0110i\u1ec1u n\u00e0y khuy\u1ebfn kh\u00edch m\u00f4 h\u00ecnh ph\u00e2n b\u1ed5 tr\u1ecdng l\u01b0\u1ee3ng \u0111\u1ed3ng \u0111\u1ec1u h\u01a1n tr\u00ean t\u1ea5t c\u1ea3 c\u00e1c t\u00ednh n\u0103ng, thay v\u00ec t\u1eadp trung nhi\u1ec1u v\u00e0o m\u1ed9t s\u1ed1 t\u00ednh n\u0103ng. N\u00f3 ng\u0103n ch\u1eb7n c\u00e1c gi\u00e1 tr\u1ecb c\u1ef1c \u0111oan v\u00e0 c\u1ea3i thi\u1ec7n s\u1ef1 \u1ed5n \u0111\u1ecbnh.<\/p>\n<h2>C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a ch\u00ednh quy h\u00f3a (L1, L2)<\/h2>\n<ol>\n<li>\n<p><strong>Ng\u0103n ng\u1eeba vi\u1ec7c trang b\u1ecb qu\u00e1 m\u1ee9c:<\/strong> C\u00e1c k\u1ef9 thu\u1eadt ch\u00ednh quy h\u00f3a l\u00e0m gi\u1ea3m \u0111\u00e1ng k\u1ec3 vi\u1ec7c trang b\u1ecb qu\u00e1 m\u1ee9c b\u1eb1ng c\u00e1ch h\u1ea1n ch\u1ebf \u0111\u1ed9 ph\u1ee9c t\u1ea1p c\u1ee7a c\u00e1c m\u00f4 h\u00ecnh, gi\u00fap ch\u00fang kh\u00e1i qu\u00e1t h\u00f3a d\u1eef li\u1ec7u m\u1edbi t\u1ed1t h\u01a1n.<\/p>\n<\/li>\n<li>\n<p><strong>L\u1ef1a ch\u1ecdn t\u00ednh n\u0103ng:<\/strong> Ch\u00ednh quy h\u00f3a L1 v\u1ed1n th\u1ef1c hi\u1ec7n l\u1ef1a ch\u1ecdn t\u00ednh n\u0103ng b\u1eb1ng c\u00e1ch \u0111\u01b0a m\u1ed9t s\u1ed1 tr\u1ecdng s\u1ed1 t\u00ednh n\u0103ng v\u1ec1 0. \u0110i\u1ec1u n\u00e0y c\u00f3 th\u1ec3 thu\u1eadn l\u1ee3i khi l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c b\u1ed9 d\u1eef li\u1ec7u nhi\u1ec1u chi\u1ec1u.<\/p>\n<\/li>\n<li>\n<p><strong>\u0110\u1ed9 \u1ed5n \u0111\u1ecbnh tham s\u1ed1:<\/strong> Ch\u00ednh quy h\u00f3a L2 n\u00e2ng cao t\u00ednh \u1ed5n \u0111\u1ecbnh c\u1ee7a \u01b0\u1edbc t\u00ednh tham s\u1ed1, l\u00e0m cho d\u1ef1 \u0111o\u00e1n c\u1ee7a m\u00f4 h\u00ecnh \u00edt nh\u1ea1y c\u1ea3m h\u01a1n v\u1edbi nh\u1eefng thay \u0111\u1ed5i nh\u1ecf trong d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o.<\/p>\n<\/li>\n<\/ol>\n<h2>C\u00e1c lo\u1ea1i ch\u00ednh quy h\u00f3a (L1, L2)<\/h2>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>C\u01a1 ch\u1ebf<\/th>\n<th>Tr\u01b0\u1eddng h\u1ee3p s\u1eed d\u1ee5ng<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Ch\u00ednh quy h\u00f3a L1 (Lasso)<\/td>\n<td>Ph\u1ea1t c\u00e1c gi\u00e1 tr\u1ecb tham s\u1ed1 tuy\u1ec7t \u0111\u1ed1i<\/td>\n<td>L\u1ef1a ch\u1ecdn t\u00ednh n\u0103ng, m\u00f4 h\u00ecnh th\u01b0a th\u1edbt<\/td>\n<\/tr>\n<tr>\n<td>Ch\u00ednh quy h\u00f3a L2 (S\u01b0\u1eddn)<\/td>\n<td>Ph\u1ea1t c\u00e1c gi\u00e1 tr\u1ecb tham s\u1ed1 b\u00ecnh ph\u01b0\u01a1ng<\/td>\n<td>C\u1ea3i thi\u1ec7n \u0111\u1ed9 \u1ed5n \u0111\u1ecbnh c\u1ee7a tham s\u1ed1, c\u00e2n b\u1eb1ng t\u1ed5ng th\u1ec3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u1ee8ng d\u1ee5ng, th\u00e1ch th\u1ee9c v\u00e0 gi\u1ea3i ph\u00e1p<\/h2>\n<p>C\u00e1c k\u1ef9 thu\u1eadt ch\u00ednh quy h\u00f3a c\u00f3 r\u1ea5t nhi\u1ec1u \u1ee9ng d\u1ee5ng, t\u1eeb h\u1ed3i quy tuy\u1ebfn t\u00ednh v\u00e0 h\u1ed3i quy logistic \u0111\u1ebfn m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh v\u00e0 h\u1ecdc s\u00e2u. Ch\u00fang \u0111\u1eb7c bi\u1ec7t h\u1eefu \u00edch khi l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c t\u1eadp d\u1eef li\u1ec7u nh\u1ecf ho\u1eb7c c\u00e1c t\u1eadp d\u1eef li\u1ec7u c\u00f3 k\u00edch th\u01b0\u1edbc t\u00ednh n\u0103ng cao. Tuy nhi\u00ean, vi\u1ec7c \u00e1p d\u1ee5ng ch\u00ednh quy h\u00f3a kh\u00f4ng ph\u1ea3i l\u00e0 kh\u00f4ng c\u00f3 nh\u1eefng th\u00e1ch th\u1ee9c:<\/p>\n<ol>\n<li>\n<p><strong>Ch\u1ecdn c\u01b0\u1eddng \u0111\u1ed9 ch\u00ednh quy h\u00f3a:<\/strong> Ng\u01b0\u1eddi ta ph\u1ea3i \u0111\u1ea1t \u0111\u01b0\u1ee3c s\u1ef1 c\u00e2n b\u1eb1ng gi\u1eefa vi\u1ec7c ng\u0103n ch\u1eb7n vi\u1ec7c trang b\u1ecb qu\u00e1 m\u1ee9c v\u00e0 kh\u00f4ng h\u1ea1n ch\u1ebf qu\u00e1 m\u1ee9c kh\u1ea3 n\u0103ng n\u1eafm b\u1eaft c\u00e1c m\u1eabu ph\u1ee9c t\u1ea1p c\u1ee7a m\u00f4 h\u00ecnh.<\/p>\n<\/li>\n<li>\n<p><strong>Kh\u1ea3 n\u0103ng gi\u1ea3i th\u00edch:<\/strong> M\u1eb7c d\u00f9 vi\u1ec7c ch\u00ednh quy h\u00f3a L1 c\u00f3 th\u1ec3 d\u1eabn \u0111\u1ebfn c\u00e1c m\u00f4 h\u00ecnh d\u1ec5 hi\u1ec3u h\u01a1n th\u00f4ng qua vi\u1ec7c l\u1ef1a ch\u1ecdn t\u00ednh n\u0103ng, nh\u01b0ng n\u00f3 c\u00f3 th\u1ec3 lo\u1ea1i b\u1ecf nh\u1eefng th\u00f4ng tin c\u00f3 th\u1ec3 h\u1eefu \u00edch.<\/p>\n<\/li>\n<\/ol>\n<h2>So s\u00e1nh v\u00e0 quan \u0111i\u1ec3m<\/h2>\n<table>\n<thead>\n<tr>\n<th>So s\u00e1nh<\/th>\n<th>Ch\u00ednh quy h\u00f3a (L1, L2)<\/th>\n<th>B\u1ecf h\u1ecdc (Ch\u00ednh quy h\u00f3a)<\/th>\n<th>Chu\u1ea9n h\u00f3a h\u00e0ng lo\u1ea1t<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>C\u01a1 ch\u1ebf<\/td>\n<td>H\u00ecnh ph\u1ea1t c\u00e2n n\u1eb7ng<\/td>\n<td>V\u00f4 hi\u1ec7u h\u00f3a n\u01a1-ron<\/td>\n<td>B\u00ecnh th\u01b0\u1eddng h\u00f3a k\u00edch ho\u1ea1t l\u1edbp<\/td>\n<\/tr>\n<tr>\n<td>Ng\u0103n ch\u1eb7n trang b\u1ecb qu\u00e1 m\u1ee9c<\/td>\n<td>\u0110\u00fang<\/td>\n<td>\u0110\u00fang<\/td>\n<td>KH\u00d4NG<\/td>\n<\/tr>\n<tr>\n<td>Kh\u1ea3 n\u0103ng gi\u1ea3i th\u00edch<\/td>\n<td>Cao (L1) \/ Trung b\u00ecnh (L2)<\/td>\n<td>Th\u1ea5p<\/td>\n<td>kh\u00f4ng \u00e1p d\u1ee5ng<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>T\u00edch h\u1ee3p m\u00e1y ch\u1ee7 proxy v\u00e0 ti\u1ec1m n\u0103ng trong t\u01b0\u01a1ng lai<\/h2>\n<p>T\u01b0\u01a1ng lai c\u1ee7a Ch\u00ednh quy h\u00f3a h\u1ee9a h\u1eb9n s\u1ebd c\u00f3 nhi\u1ec1u h\u1ee9a h\u1eb9n khi c\u00f4ng ngh\u1ec7 ti\u1ebfn b\u1ed9. Khi d\u1eef li\u1ec7u ti\u1ebfp t\u1ee5c ph\u00e1t tri\u1ec3n v\u1ec1 \u0111\u1ed9 ph\u1ee9c t\u1ea1p v\u00e0 nhi\u1ec1u chi\u1ec1u, nhu c\u1ea7u v\u1ec1 c\u00e1c k\u1ef9 thu\u1eadt n\u00e2ng cao kh\u1ea3 n\u0103ng kh\u00e1i qu\u00e1t h\u00f3a m\u00f4 h\u00ecnh c\u00e0ng tr\u1edf n\u00ean quan tr\u1ecdng h\u01a1n. Trong l\u0129nh v\u1ef1c cung c\u1ea5p m\u00e1y ch\u1ee7 proxy, c\u00e1c k\u1ef9 thu\u1eadt Ch\u00ednh quy h\u00f3a c\u00f3 th\u1ec3 \u0111\u00f3ng vai tr\u00f2 t\u1ed1i \u01b0u h\u00f3a vi\u1ec7c ph\u00e2n b\u1ed5 t\u00e0i nguy\u00ean, c\u00e2n b\u1eb1ng t\u1ea3i v\u00e0 c\u1ea3i thi\u1ec7n t\u00ednh b\u1ea3o m\u1eadt c\u1ee7a ph\u00e2n t\u00edch l\u01b0u l\u01b0\u1ee3ng m\u1ea1ng.<\/p>\n<h2>Ph\u1ea7n k\u1ebft lu\u1eadn<\/h2>\n<p>Ch\u00ednh quy h\u00f3a (L1, L2) \u0111\u01b0\u1ee3c coi l\u00e0 n\u1ec1n t\u1ea3ng trong l\u0129nh v\u1ef1c h\u1ecdc m\u00e1y, cung c\u1ea5p c\u00e1c gi\u1ea3i ph\u00e1p hi\u1ec7u qu\u1ea3 cho v\u1ea5n \u0111\u1ec1 trang b\u1ecb qu\u00e1 m\u1ee9c v\u00e0 \u0111\u1ed9 ph\u1ee9c t\u1ea1p c\u1ee7a m\u00f4 h\u00ecnh. C\u00e1c k\u1ef9 thu\u1eadt ch\u00ednh quy h\u00f3a L1 v\u00e0 L2 \u0111\u00e3 t\u00ecm \u0111\u01b0\u1ee3c \u0111\u01b0\u1eddng v\u00e0o c\u00e1c \u1ee9ng d\u1ee5ng \u0111a d\u1ea1ng, c\u00f3 ti\u1ec1m n\u0103ng c\u00e1ch m\u1ea1ng h\u00f3a c\u00e1c l\u0129nh v\u1ef1c nh\u01b0 cung c\u1ea5p m\u00e1y ch\u1ee7 proxy. Khi c\u00f4ng ngh\u1ec7 ti\u1ebfn l\u00ean ph\u00eda tr\u01b0\u1edbc, vi\u1ec7c t\u00edch h\u1ee3p c\u00e1c k\u1ef9 thu\u1eadt Ch\u00ednh quy h\u00f3a v\u1edbi c\u00e1c c\u00f4ng ngh\u1ec7 ti\u00ean ti\u1ebfn ch\u1eafc ch\u1eafn s\u1ebd d\u1eabn \u0111\u1ebfn n\u00e2ng cao hi\u1ec7u qu\u1ea3 v\u00e0 hi\u1ec7u su\u1ea5t tr\u00ean nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<p>\u0110\u1ec3 bi\u1ebft th\u00eam th\u00f4ng tin chuy\u00ean s\u00e2u v\u1ec1 Ch\u00ednh quy h\u00f3a (L1, L2) v\u00e0 c\u00e1c \u1ee9ng d\u1ee5ng c\u1ee7a n\u00f3, h\u00e3y xem x\u00e9t kh\u00e1m ph\u00e1 c\u00e1c t\u00e0i nguy\u00ean sau:<\/p>\n<ul>\n<li><a href=\"https:\/\/web.stanford.edu\/~hastie\/StatLearnSparsity_files\/SLS.pdf\" target=\"_new\" rel=\"noopener nofollow\">\u0110\u1ea1i h\u1ecdc Stanford: Ch\u00ednh quy h\u00f3a<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/modules\/linear_model.html#regularization\" target=\"_new\" rel=\"noopener nofollow\">T\u00e0i li\u1ec7u Scikit-learn: Ch\u00ednh quy h\u00f3a<\/a><\/li>\n<li><a href=\"https:\/\/towardsdatascience.com\/introduction-to-regularization-in-machine-learning-91e094a367d5\" target=\"_new\" rel=\"noopener nofollow\">H\u01b0\u1edbng t\u1edbi khoa h\u1ecdc d\u1eef li\u1ec7u: Gi\u1edbi thi\u1ec7u v\u1ec1 ch\u00ednh quy h\u00f3a trong h\u1ecdc m\u00e1y<\/a><\/li>\n<\/ul>\n<p>Lu\u00f4n c\u1eadp nh\u1eadt v\u1ec1 nh\u1eefng ti\u1ebfn b\u1ed9 m\u1edbi nh\u1ea5t trong h\u1ecdc m\u00e1y, ph\u00e2n t\u00edch d\u1eef li\u1ec7u v\u00e0 c\u00f4ng ngh\u1ec7 m\u00e1y ch\u1ee7 proxy b\u1eb1ng c\u00e1ch truy c\u1eadp <a href=\"https:\/\/oneproxy.pro\/vn\/blog\/\" target=\"_new\" rel=\"noopener\">OneProxy<\/a> th\u01b0\u1eddng xuy\u00ean.<\/p>","protected":false},"featured_media":0,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478675","wiki","type-wiki","status-publish","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Regularization (L1, L2): Enhancing Proxy Server Performance<\/mark>","faq_items":[{"question":"What is Regularization, and why is it important in machine learning?","answer":"<p>Regularization is a technique used in machine learning to prevent overfitting, which occurs when a model becomes too tailored to the training data and struggles to generalize well on new data. It involves adding penalty terms to the model's loss function, curbing the complexity of the model and enhancing its ability to generalize to unseen data.<\/p>"},{"question":"What are L1 and L2 regularization, and how do they work?","answer":"<p>L1 regularization (Lasso) and L2 regularization (Ridge) are two prominent types of regularization. L1 introduces a penalty based on the absolute values of parameter weights, driving some weights to zero and performing feature selection. L2 adds a penalty based on the squared values of parameter weights, distributing weights more evenly across features and improving stability.<\/p>"},{"question":"What are the key benefits of using regularization?","answer":"<p>Regularization techniques offer several advantages, including preventing overfitting, enhancing model stability, and promoting generalization to new data. L1 regularization aids in feature selection, while L2 regularization balances parameter values.<\/p>"},{"question":"How do L1 and L2 regularization differ in their effects on model interpretability?","answer":"<p>L1 regularization tends to lead to higher model interpretability due to its feature selection capability. It can help identify the most relevant features by driving some feature weights to zero. L2 regularization, while promoting stability, may not directly provide the same level of interpretability.<\/p>"},{"question":"What are the challenges in applying regularization?","answer":"<p>Choosing the right strength of regularization is crucial; too much can lead to underfitting, while too little may not prevent overfitting effectively. Additionally, L1 regularization might discard useful information along with noisy features.<\/p>"},{"question":"How can regularization techniques impact proxy server provision?","answer":"<p>In the realm of proxy server provision, regularization techniques could optimize resource allocation, load balancing, and enhance security in network traffic analysis. Regularization could contribute to efficient and secure proxy server operation.<\/p>"},{"question":"How can I learn more about regularization and its applications?","answer":"<p>For a deeper understanding of regularization (L1, L2) and its applications, you can explore resources such as the Stanford University documentation on regularization, the Scikit-learn documentation on linear models, and informative articles on platforms like Towards Data Science. Stay informed about the latest advancements by visiting OneProxy's blog regularly.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478675","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478675\/revisions"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478675"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}