{"id":477830,"date":"2023-08-09T09:21:11","date_gmt":"2023-08-09T09:21:11","guid":{"rendered":""},"modified":"2023-09-05T11:15:32","modified_gmt":"2023-09-05T11:15:32","slug":"linear-discriminant-analysis","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/linear-discriminant-analysis\/","title":{"rendered":"Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh"},"content":{"rendered":"

Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh (LDA) l\u00e0 m\u1ed9t ph\u01b0\u01a1ng ph\u00e1p th\u1ed1ng k\u00ea \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong h\u1ecdc m\u00e1y v\u00e0 nh\u1eadn d\u1ea1ng m\u1eabu \u0111\u1ec3 t\u00ecm ra s\u1ef1 k\u1ebft h\u1ee3p tuy\u1ebfn t\u00ednh c\u1ee7a c\u00e1c t\u00ednh n\u0103ng gi\u00fap ph\u00e2n t\u00e1ch t\u1ed1t nh\u1ea5t hai ho\u1eb7c nhi\u1ec1u l\u1edbp. N\u00f3 nh\u1eb1m m\u1ee5c \u0111\u00edch chi\u1ebfu d\u1eef li\u1ec7u l\u00ean m\u1ed9t kh\u00f4ng gian c\u00f3 chi\u1ec1u th\u1ea5p h\u01a1n trong khi v\u1eabn b\u1ea3o to\u00e0n th\u00f4ng tin ph\u00e2n bi\u1ec7t l\u1edbp. LDA \u0111\u00e3 \u0111\u01b0\u1ee3c ch\u1ee9ng minh l\u00e0 m\u1ed9t c\u00f4ng c\u1ee5 m\u1ea1nh m\u1ebd trong nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau, bao g\u1ed3m nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t, tin sinh h\u1ecdc v\u00e0 ph\u00e2n lo\u1ea1i t\u00e0i li\u1ec7u.<\/p>\n

L\u1ecbch s\u1eed ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

Ngu\u1ed3n g\u1ed1c c\u1ee7a Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh c\u00f3 th\u1ec3 b\u1eaft ngu\u1ed3n t\u1eeb \u0111\u1ea7u nh\u1eefng n\u0103m 1930 khi Ronald A. Fisher l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u01b0a ra kh\u00e1i ni\u1ec7m Ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh c\u1ee7a Fisher. C\u00f4ng tr\u00ecnh ban \u0111\u1ea7u c\u1ee7a Fisher \u0111\u00e3 \u0111\u1eb7t n\u1ec1n m\u00f3ng cho LDA v\u00e0 n\u00f3 \u0111\u01b0\u1ee3c c\u00f4ng nh\u1eadn r\u1ed9ng r\u00e3i nh\u01b0 m\u1ed9t ph\u01b0\u01a1ng ph\u00e1p c\u01a1 b\u1ea3n trong l\u0129nh v\u1ef1c th\u1ed1ng k\u00ea v\u00e0 ph\u00e2n lo\u1ea1i m\u1eabu.<\/p>\n

Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt gi\u1ea3m k\u00edch th\u01b0\u1edbc c\u00f3 gi\u00e1m s\u00e1t. N\u00f3 ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch t\u1ed1i \u0111a h\u00f3a t\u1ef7 l\u1ec7 c\u1ee7a ma tr\u1eadn ph\u00e2n t\u00e1n gi\u1eefa c\u00e1c l\u1edbp v\u1edbi ma tr\u1eadn ph\u00e2n t\u00e1n trong l\u1edbp. S\u1ef1 ph\u00e2n t\u00e1n gi\u1eefa c\u00e1c l\u1edbp bi\u1ec3u th\u1ecb ph\u01b0\u01a1ng sai gi\u1eefa c\u00e1c l\u1edbp kh\u00e1c nhau, trong khi s\u1ef1 ph\u00e2n t\u00e1n trong l\u1edbp bi\u1ec3u th\u1ecb ph\u01b0\u01a1ng sai trong m\u1ed7i l\u1edbp. B\u1eb1ng c\u00e1ch t\u1ed1i \u0111a h\u00f3a t\u1ef7 l\u1ec7 n\u00e0y, LDA \u0111\u1ea3m b\u1ea3o r\u1eb1ng c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u c\u1ee7a c\u00e1c l\u1edbp kh\u00e1c nhau \u0111\u01b0\u1ee3c ph\u00e2n t\u00e1ch r\u00f5 r\u00e0ng, d\u1eabn \u0111\u1ebfn vi\u1ec7c ph\u00e2n t\u00e1ch l\u1edbp hi\u1ec7u qu\u1ea3.<\/p>\n

LDA gi\u1ea3 \u0111\u1ecbnh r\u1eb1ng d\u1eef li\u1ec7u tu\u00e2n theo ph\u00e2n ph\u1ed1i Gaussian v\u00e0 ma tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai c\u1ee7a c\u00e1c l\u1edbp l\u00e0 b\u1eb1ng nhau. N\u00f3 chi\u1ebfu d\u1eef li\u1ec7u v\u00e0o kh\u00f4ng gian c\u00f3 chi\u1ec1u th\u1ea5p h\u01a1n \u0111\u1ed3ng th\u1eddi t\u1ed1i \u0111a h\u00f3a kh\u1ea3 n\u0103ng ph\u00e2n t\u00e1ch l\u1edbp. Sau \u0111\u00f3, c\u00e1c ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh thu \u0111\u01b0\u1ee3c s\u1ebd \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 ph\u00e2n lo\u1ea1i c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u m\u1edbi v\u00e0o c\u00e1c l\u1edbp th\u00edch h\u1ee3p.<\/p>\n

C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh bao g\u1ed3m c\u00e1c b\u01b0\u1edbc sau:<\/p>\n

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  1. \n

    T\u00ednh to\u00e1n ph\u01b0\u01a1ng ti\u1ec7n l\u1edbp<\/strong>: T\u00ednh c\u00e1c vect\u01a1 trung b\u00ecnh c\u1ee7a t\u1eebng l\u1edbp trong kh\u00f4ng gian \u0111\u1eb7c tr\u01b0ng ban \u0111\u1ea7u.<\/p>\n<\/li>\n

  2. \n

    T\u00ednh to\u00e1n ma tr\u1eadn ph\u00e2n t\u00e1n<\/strong>: T\u00ednh ma tr\u1eadn ph\u00e2n t\u00e1n trong l\u1edbp v\u00e0 ma tr\u1eadn ph\u00e2n t\u00e1n gi\u1eefa c\u00e1c l\u1edbp.<\/p>\n<\/li>\n

  3. \n

    Ph\u00e2n t\u00edch gi\u00e1 tr\u1ecb ri\u00eang<\/strong>: Th\u1ef1c hi\u1ec7n ph\u00e2n t\u00e1ch gi\u00e1 tr\u1ecb ri\u00eang tr\u00ean t\u00edch ngh\u1ecbch \u0111\u1ea3o c\u1ee7a ma tr\u1eadn ph\u00e2n t\u00e1n trong l\u1edbp v\u00e0 ma tr\u1eadn ph\u00e2n t\u00e1n gi\u1eefa c\u00e1c l\u1edbp.<\/p>\n<\/li>\n

  4. \n

    Ch\u1ecdn ng\u01b0\u1eddi ph\u00e2n bi\u1ec7t \u0111\u1ed1i x\u1eed<\/strong>: Ch\u1ecdn k vect\u01a1 ri\u00eang \u0111\u1ec9nh t\u01b0\u01a1ng \u1ee9ng v\u1edbi gi\u00e1 tr\u1ecb ri\u00eang l\u1edbn nh\u1ea5t \u0111\u1ec3 t\u1ea1o th\u00e0nh ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh.<\/p>\n<\/li>\n

  5. \n

    D\u1eef li\u1ec7u d\u1ef1 \u00e1n<\/strong>: Chi\u1ebfu c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u l\u00ean kh\u00f4ng gian con m\u1edbi \u0111\u01b0\u1ee3c m\u1edf r\u1ed9ng b\u1edfi c\u00e1c ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh.<\/p>\n<\/li>\n<\/ol>\n

    Ph\u00e2n t\u00edch c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh c\u1ee7a ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

    Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh cung c\u1ea5p m\u1ed9t s\u1ed1 t\u00ednh n\u0103ng ch\u00ednh khi\u1ebfn n\u00f3 tr\u1edf th\u00e0nh l\u1ef1a ch\u1ecdn ph\u1ed5 bi\u1ebfn trong c\u00e1c nhi\u1ec7m v\u1ee5 ph\u00e2n lo\u1ea1i:<\/p>\n

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    1. \n

      Ph\u01b0\u01a1ng ph\u00e1p gi\u00e1m s\u00e1t<\/strong>: LDA l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt h\u1ecdc c\u00f3 gi\u00e1m s\u00e1t, c\u00f3 ngh\u0129a l\u00e0 n\u00f3 y\u00eau c\u1ea7u d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n trong qu\u00e1 tr\u00ecnh \u0111\u00e0o t\u1ea1o.<\/p>\n<\/li>\n

    2. \n

      Gi\u1ea3m k\u00edch th\u01b0\u1edbc<\/strong>: LDA l\u00e0m gi\u1ea3m t\u00ednh chi\u1ec1u c\u1ee7a d\u1eef li\u1ec7u, gi\u00fap d\u1eef li\u1ec7u c\u00f3 hi\u1ec7u qu\u1ea3 t\u00ednh to\u00e1n \u0111\u1ed1i v\u1edbi c\u00e1c t\u1eadp d\u1eef li\u1ec7u l\u1edbn.<\/p>\n<\/li>\n

    3. \n

      T\u00e1ch t\u1ed1i \u01b0u<\/strong>: N\u00f3 nh\u1eb1m m\u1ee5c \u0111\u00edch t\u00ecm ra s\u1ef1 k\u1ebft h\u1ee3p tuy\u1ebfn t\u00ednh t\u1ed1i \u01b0u c\u1ee7a c\u00e1c t\u00ednh n\u0103ng nh\u1eb1m t\u1ed1i \u0111a h\u00f3a kh\u1ea3 n\u0103ng ph\u00e2n t\u00e1ch l\u1edbp.<\/p>\n<\/li>\n

    4. \n

      Ph\u00e2n lo\u1ea1i<\/strong>: LDA c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho c\u00e1c nhi\u1ec7m v\u1ee5 ph\u00e2n lo\u1ea1i b\u1eb1ng c\u00e1ch g\u00e1n c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u m\u1edbi cho l\u1edbp c\u00f3 gi\u00e1 tr\u1ecb trung b\u00ecnh g\u1ea7n nh\u1ea5t trong kh\u00f4ng gian c\u00f3 chi\u1ec1u th\u1ea5p h\u01a1n.<\/p>\n<\/li>\n<\/ol>\n

      C\u00e1c lo\u1ea1i ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

      C\u00f3 nhi\u1ec1u bi\u1ebfn th\u1ec3 kh\u00e1c nhau c\u1ee7a Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh, bao g\u1ed3m:<\/p>\n

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      1. \n

        LDA c\u1ee7a Fisher<\/strong>: C\u00f4ng th\u1ee9c ban \u0111\u1ea7u do RA Fisher \u0111\u1ec1 xu\u1ea5t, gi\u1ea3 \u0111\u1ecbnh r\u1eb1ng c\u00e1c ma tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai c\u1ee7a l\u1edbp l\u00e0 b\u1eb1ng nhau.<\/p>\n<\/li>\n

      2. \n

        LDA ch\u00ednh quy<\/strong>: M\u1ed9t ti\u1ec7n \u00edch m\u1edf r\u1ed9ng gi\u1ea3i quy\u1ebft c\u00e1c v\u1ea5n \u0111\u1ec1 v\u1ec1 \u0111i\u1ec3m k\u1ef3 d\u1ecb trong ma tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai b\u1eb1ng c\u00e1ch th\u00eam c\u00e1c thu\u1eadt ng\u1eef ch\u00ednh quy h\u00f3a.<\/p>\n<\/li>\n

      3. \n

        Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t b\u1eadc hai (QDA)<\/strong>: M\u1ed9t bi\u1ebfn th\u1ec3 gi\u00fap n\u1edbi l\u1ecfng gi\u1ea3 \u0111\u1ecbnh v\u1ec1 ma tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai l\u1edbp b\u1eb1ng nhau v\u00e0 cho ph\u00e9p c\u00e1c ranh gi\u1edbi quy\u1ebft \u0111\u1ecbnh b\u1eadc hai.<\/p>\n<\/li>\n

      4. \n

        Ph\u00e2n t\u00edch \u0111a ph\u00e2n bi\u1ec7t (MDA)<\/strong>: M\u1ed9t ph\u1ea7n m\u1edf r\u1ed9ng c\u1ee7a LDA xem x\u00e9t nhi\u1ec1u bi\u1ebfn ph\u1ee5 thu\u1ed9c.<\/p>\n<\/li>\n

      5. \n

        Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t linh ho\u1ea1t (FDA)<\/strong>: M\u1ed9t ph\u1ea7n m\u1edf r\u1ed9ng phi tuy\u1ebfn t\u00ednh c\u1ee7a LDA s\u1eed d\u1ee5ng c\u00e1c ph\u01b0\u01a1ng th\u1ee9c kernel \u0111\u1ec3 ph\u00e2n lo\u1ea1i.<\/p>\n<\/li>\n<\/ol>\n

        D\u01b0\u1edbi \u0111\u00e2y l\u00e0 b\u1ea3ng so s\u00e1nh c\u00e1c lo\u1ea1i n\u00e0y:<\/p>\n\n\n\n\n\n\n\n\n\n
        Ki\u1ec3u<\/th>\nGi\u1ea3 thi\u1ebft<\/th>\nRanh gi\u1edbi quy\u1ebft \u0111\u1ecbnh<\/th>\n<\/tr>\n<\/thead>\n
        LDA c\u1ee7a Fisher<\/td>\nMa tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai l\u1edbp b\u1eb1ng nhau<\/td>\ntuy\u1ebfn t\u00ednh<\/td>\n<\/tr>\n
        LDA ch\u00ednh quy<\/td>\nMa tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai ch\u00ednh quy<\/td>\ntuy\u1ebfn t\u00ednh<\/td>\n<\/tr>\n
        Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t b\u1eadc hai (QDA)<\/td>\nMa tr\u1eadn hi\u1ec7p ph\u01b0\u01a1ng sai l\u1edbp kh\u00e1c nhau<\/td>\nb\u1eadc hai<\/td>\n<\/tr>\n
        Ph\u00e2n t\u00edch \u0111a ph\u00e2n bi\u1ec7t (MDA)<\/td>\nNhi\u1ec1u bi\u1ebfn ph\u1ee5 thu\u1ed9c<\/td>\nTuy\u1ebfn t\u00ednh ho\u1eb7c b\u1eadc hai<\/td>\n<\/tr>\n
        Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t linh ho\u1ea1t (FDA)<\/td>\nChuy\u1ec3n \u0111\u1ed5i d\u1eef li\u1ec7u phi tuy\u1ebfn t\u00ednh<\/td>\nPhi tuy\u1ebfn t\u00ednh<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        C\u00e1ch s\u1eed d\u1ee5ng ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh v\u00e0 nh\u1eefng th\u00e1ch th\u1ee9c li\u00ean quan<\/h2>\n

        Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh t\u00ecm th\u1ea5y nhi\u1ec1u \u1ee9ng d\u1ee5ng tr\u00ean nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau:<\/p>\n

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        1. \n

          Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/strong>: LDA \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng r\u1ed9ng r\u00e3i trong c\u00e1c h\u1ec7 th\u1ed1ng nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t \u0111\u1ec3 tr\u00edch xu\u1ea5t c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ph\u00e2n bi\u1ec7t nh\u1eb1m nh\u1eadn d\u1ea1ng c\u00e1 nh\u00e2n.<\/p>\n<\/li>\n

        2. \n

          Ph\u00e2n lo\u1ea1i t\u00e0i li\u1ec7u<\/strong>: N\u00f3 c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 ph\u00e2n lo\u1ea1i t\u00e0i li\u1ec7u v\u0103n b\u1ea3n th\u00e0nh c\u00e1c l\u1edbp kh\u00e1c nhau d\u1ef1a tr\u00ean n\u1ed9i dung c\u1ee7a ch\u00fang.<\/p>\n<\/li>\n

        3. \n

          Ph\u00e2n t\u00edch d\u1eef li\u1ec7u y sinh<\/strong>: LDA h\u1ed7 tr\u1ee3 x\u00e1c \u0111\u1ecbnh d\u1ea5u \u1ea5n sinh h\u1ecdc v\u00e0 ph\u00e2n lo\u1ea1i d\u1eef li\u1ec7u y t\u1ebf.<\/p>\n<\/li>\n<\/ol>\n

          Nh\u1eefng th\u00e1ch th\u1ee9c li\u00ean quan \u0111\u1ebfn LDA bao g\u1ed3m:<\/p>\n

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          1. \n

            Gi\u1ea3 \u0111\u1ecbnh tuy\u1ebfn t\u00ednh<\/strong>: LDA c\u00f3 th\u1ec3 kh\u00f4ng ho\u1ea1t \u0111\u1ed9ng t\u1ed1t khi c\u00e1c l\u1edbp c\u00f3 m\u1ed1i quan h\u1ec7 phi tuy\u1ebfn t\u00ednh ph\u1ee9c t\u1ea1p.<\/p>\n<\/li>\n

          2. \n

            L\u1eddi nguy\u1ec1n c\u1ee7a chi\u1ec1u<\/strong>: Trong kh\u00f4ng gian nhi\u1ec1u chi\u1ec1u, LDA c\u00f3 th\u1ec3 b\u1ecb trang b\u1ecb qu\u00e1 m\u1ee9c do s\u1ed1 l\u01b0\u1ee3ng \u0111i\u1ec3m d\u1eef li\u1ec7u b\u1ecb h\u1ea1n ch\u1ebf.<\/p>\n<\/li>\n

          3. \n

            D\u1eef li\u1ec7u m\u1ea5t c\u00e2n b\u1eb1ng<\/strong>: Hi\u1ec7u su\u1ea5t c\u1ee7a LDA c\u00f3 th\u1ec3 b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi s\u1ef1 ph\u00e2n b\u1ed5 l\u1edbp kh\u00f4ng c\u00e2n b\u1eb1ng.<\/p>\n<\/li>\n<\/ol>\n

            \u0110\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 so s\u00e1nh<\/h2>\n

            \u0110\u00e2y l\u00e0 so s\u00e1nh LDA v\u1edbi c\u00e1c thu\u1eadt ng\u1eef li\u00ean quan kh\u00e1c:<\/p>\n\n\n\n\n\n\n\n\n
            \u0111\u1eb7c tr\u01b0ng<\/th>\nPh\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/th>\nPh\u00e2n t\u00edch th\u00e0nh ph\u1ea7n ch\u00ednh (PCA)<\/th>\nPh\u00e2n t\u00edch ph\u00e2n bi\u1ec7t b\u1eadc hai (QDA)<\/th>\n<\/tr>\n<\/thead>\n
            Lo\u1ea1i ph\u01b0\u01a1ng ph\u00e1p<\/td>\nGi\u00e1m s\u00e1t<\/td>\nKh\u00f4ng \u0111\u01b0\u1ee3c gi\u00e1m s\u00e1t<\/td>\nGi\u00e1m s\u00e1t<\/td>\n<\/tr>\n
            M\u1ee5c ti\u00eau<\/td>\nKh\u1ea3 n\u0103ng ph\u00e2n t\u00e1ch l\u1edbp<\/td>\nT\u1ed1i \u0111a h\u00f3a ph\u01b0\u01a1ng sai<\/td>\nKh\u1ea3 n\u0103ng ph\u00e2n t\u00e1ch l\u1edbp<\/td>\n<\/tr>\n
            Ranh gi\u1edbi quy\u1ebft \u0111\u1ecbnh<\/td>\ntuy\u1ebfn t\u00ednh<\/td>\ntuy\u1ebfn t\u00ednh<\/td>\nb\u1eadc hai<\/td>\n<\/tr>\n
            Gi\u1ea3 \u0111\u1ecbnh v\u1ec1 hi\u1ec7p ph\u01b0\u01a1ng sai<\/td>\nHi\u1ec7p ph\u01b0\u01a1ng sai b\u1eb1ng nhau<\/td>\nKh\u00f4ng c\u00f3 gi\u1ea3 \u0111\u1ecbnh<\/td>\nHi\u1ec7p ph\u01b0\u01a1ng sai kh\u00e1c nhau<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

            Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 t\u01b0\u01a1ng lai<\/h2>\n

            Khi h\u1ecdc m\u00e1y v\u00e0 nh\u1eadn d\u1ea1ng m\u1eabu ti\u1ebfp t\u1ee5c ph\u00e1t tri\u1ec3n, Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh c\u00f3 th\u1ec3 v\u1eabn l\u00e0 m\u1ed9t c\u00f4ng c\u1ee5 c\u00f3 gi\u00e1 tr\u1ecb. Nghi\u00ean c\u1ee9u trong l\u0129nh v\u1ef1c n\u00e0y nh\u1eb1m m\u1ee5c \u0111\u00edch gi\u1ea3i quy\u1ebft nh\u1eefng h\u1ea1n ch\u1ebf c\u1ee7a LDA, ch\u1eb3ng h\u1ea1n nh\u01b0 x\u1eed l\u00fd c\u00e1c m\u1ed1i quan h\u1ec7 phi tuy\u1ebfn t\u00ednh v\u00e0 th\u00edch \u1ee9ng v\u1edbi d\u1eef li\u1ec7u kh\u00f4ng c\u00e2n b\u1eb1ng. Vi\u1ec7c t\u00edch h\u1ee3p LDA v\u1edbi c\u00e1c k\u1ef9 thu\u1eadt h\u1ecdc s\u00e2u ti\u00ean ti\u1ebfn c\u00f3 th\u1ec3 m\u1edf ra nh\u1eefng kh\u1ea3 n\u0103ng m\u1edbi cho c\u00e1c h\u1ec7 th\u1ed1ng ph\u00e2n lo\u1ea1i m\u1ea1nh m\u1ebd v\u00e0 ch\u00ednh x\u00e1c h\u01a1n.<\/p>\n

            M\u00e1y ch\u1ee7 proxy v\u00e0 ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/h2>\n

            M\u1eb7c d\u00f9 B\u1ea3n th\u00e2n Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh kh\u00f4ng li\u00ean quan tr\u1ef1c ti\u1ebfp \u0111\u1ebfn m\u00e1y ch\u1ee7 proxy nh\u01b0ng n\u00f3 c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau li\u00ean quan \u0111\u1ebfn m\u00e1y ch\u1ee7 proxy. V\u00ed d\u1ee5: LDA c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 ph\u00e2n t\u00edch v\u00e0 ph\u00e2n lo\u1ea1i d\u1eef li\u1ec7u l\u01b0u l\u01b0\u1ee3ng truy c\u1eadp m\u1ea1ng \u0111i qua m\u00e1y ch\u1ee7 proxy \u0111\u1ec3 ph\u00e1t hi\u1ec7n c\u00e1c ho\u1ea1t \u0111\u1ed9ng b\u1ea5t th\u01b0\u1eddng ho\u1eb7c \u0111\u00e1ng ng\u1edd. N\u00f3 c\u0169ng c\u00f3 th\u1ec3 gi\u00fap ph\u00e2n lo\u1ea1i n\u1ed9i dung web d\u1ef1a tr\u00ean d\u1eef li\u1ec7u thu \u0111\u01b0\u1ee3c th\u00f4ng qua m\u00e1y ch\u1ee7 proxy, h\u1ed7 tr\u1ee3 l\u1ecdc n\u1ed9i dung v\u00e0 c\u00e1c d\u1ecbch v\u1ee5 ki\u1ec3m so\u00e1t c\u1ee7a ph\u1ee5 huynh.<\/p>\n

            Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n

            \u0110\u1ec3 bi\u1ebft th\u00eam th\u00f4ng tin v\u1ec1 Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh, b\u1ea1n c\u00f3 th\u1ec3 kh\u00e1m ph\u00e1 c\u00e1c t\u00e0i nguy\u00ean sau:<\/p>\n

              \n
            1. Wikipedia - Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/a><\/li>\n
            2. \u0110\u1ea1i h\u1ecdc Stanford - H\u01b0\u1edbng d\u1eabn LDA<\/a><\/li>\n
            3. Scikit-learn \u2013 T\u00e0i li\u1ec7u LDA<\/a><\/li>\n
            4. H\u01b0\u1edbng t\u1edbi khoa h\u1ecdc d\u1eef li\u1ec7u - Gi\u1edbi thi\u1ec7u v\u1ec1 ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh<\/a><\/li>\n<\/ol>\n

              T\u00f3m l\u1ea1i, Ph\u00e2n t\u00edch ph\u00e2n bi\u1ec7t tuy\u1ebfn t\u00ednh l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt m\u1ea1nh m\u1ebd \u0111\u1ec3 gi\u1ea3m k\u00edch th\u01b0\u1edbc v\u00e0 ph\u00e2n lo\u1ea1i, c\u00f3 l\u1ecbch s\u1eed phong ph\u00fa v\u1ec1 th\u1ed1ng k\u00ea v\u00e0 nh\u1eadn d\u1ea1ng m\u1eabu. Kh\u1ea3 n\u0103ng t\u00ecm ki\u1ebfm c\u00e1c t\u1ed5 h\u1ee3p t\u00ednh n\u0103ng tuy\u1ebfn t\u00ednh t\u1ed1i \u01b0u khi\u1ebfn n\u00f3 tr\u1edf th\u00e0nh m\u1ed9t c\u00f4ng c\u1ee5 c\u00f3 gi\u00e1 tr\u1ecb trong nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau, bao g\u1ed3m nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t, ph\u00e2n lo\u1ea1i t\u00e0i li\u1ec7u v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u y sinh. Khi c\u00f4ng ngh\u1ec7 ti\u1ebfp t\u1ee5c ph\u00e1t tri\u1ec3n, LDA d\u1ef1 ki\u1ebfn s\u1ebd v\u1eabn ph\u00f9 h\u1ee3p v\u00e0 t\u00ecm ra c\u00e1c \u1ee9ng d\u1ee5ng m\u1edbi trong vi\u1ec7c gi\u1ea3i quy\u1ebft c\u00e1c v\u1ea5n \u0111\u1ec1 ph\u1ee9c t\u1ea1p trong th\u1ebf gi\u1edbi th\u1ef1c.<\/p>","protected":false},"featured_media":468777,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477830","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Linear Discriminant Analysis<\/mark>","faq_items":[{"question":"What is Linear Discriminant Analysis (LDA)?","answer":"

              Linear Discriminant Analysis (LDA) is a statistical method used in machine learning and pattern recognition. It aims to find a linear combination of features that effectively separates different classes in the data.<\/p>"},{"question":"Who introduced Linear Discriminant Analysis?","answer":"

              Linear Discriminant Analysis was introduced by Ronald A. Fisher in the early 1930s. His original work laid the foundation for this fundamental method in statistics and pattern classification.<\/p>"},{"question":"How does Linear Discriminant Analysis work?","answer":"

              LDA works by maximizing the ratio of between-class scatter to within-class scatter. It projects the data onto a lower-dimensional space while preserving class-discriminatory information, leading to improved class separation.<\/p>"},{"question":"What are the key features of Linear Discriminant Analysis?","answer":"

              Some key features of LDA include supervised learning, dimensionality reduction, optimal separation of classes, and its application in various domains such as face recognition and document classification.<\/p>"},{"question":"What types of Linear Discriminant Analysis exist?","answer":"

              Different types of LDA include Fisher's LDA, regularized LDA, quadratic discriminant analysis (QDA), multiple discriminant analysis (MDA), and flexible discriminant analysis (FDA).<\/p>"},{"question":"In what ways can Linear Discriminant Analysis be used?","answer":"

              LDA finds applications in face recognition, document classification, and biomedical data analysis, among other fields.<\/p>"},{"question":"What challenges are associated with using Linear Discriminant Analysis?","answer":"

              Challenges with LDA include its assumption of linearity, susceptibility to overfitting in high-dimensional spaces, and sensitivity to imbalanced class distributions.<\/p>"},{"question":"How does Linear Discriminant Analysis compare to other methods like PCA and QDA?","answer":"

              LDA is a supervised method focusing on class separability, while Principal Component Analysis (PCA) is an unsupervised technique aiming to maximize variance. QDA, on the other hand, allows for different class covariance matrices.<\/p>"},{"question":"What are the future perspectives for Linear Discriminant Analysis?","answer":"

              As technology advances, researchers aim to address LDA's limitations and integrate it with deep learning techniques for more robust classification systems.<\/p>"},{"question":"How can Linear Discriminant Analysis be associated with proxy servers?","answer":"

              While LDA is not directly related to proxy servers, it can be applied in analyzing network traffic passing through proxy servers to detect anomalies or categorize web content for filtering and parental control.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477830","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\/477830\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/468777"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=477830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}