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seikenn id:seikenn

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ç·šå½¢åˆ†é¡žå™¨ï¼ˆè‹±: Linear classifierï¼‰ã¯ã€ç‰¹å¾´ã®ç·šå½¢çµåˆã®å€¤ã«åŸºã¥ã„ã¦åˆ†é¡žã‚’è¡Œã†ç¢ºçŽ‡çš„åˆ†é¡žå™¨ã§ã‚ã‚‹ã€‚æ©Ÿæ¢°å¦ç¿’ã«ãŠã„ã¦ã€åˆ†é¡žã¯é …ç›®ç¾¤ã‚’ç‰¹å¾´å€¤ã«åŸºã¥ã„ã¦ã‚°ãƒ«ãƒ¼ãƒ—ã«åˆ†é¡žã™ã‚‹ã“ã¨ã‚’ç›®çš„ã¨ã™ã‚‹ã€‚ åˆ†é¡žå™¨ã¸ã®å…¥åŠ›ç‰¹å¾´ãƒ™ã‚¯ãƒˆãƒ«ãŒå®Ÿæ•°ãƒ™ã‚¯ãƒˆãƒ« ã§ã‚ã‚‹ã¨ãã€å‡ºåŠ›ã®ã‚¹ã‚³ã‚¢ã¯æ¬¡ã®ã‚ˆã†ã«ãªã‚‹ã€‚ ã“ã“ã§ã€ ã¯é‡ã¿ä»˜ã‘ã®å®Ÿæ•°ãƒ™ã‚¯ãƒˆãƒ«ã€f ã¯2ã¤ã®ãƒ™ã‚¯ãƒˆãƒ«ã®ãƒ‰ãƒƒãƒˆç©ã‚’å¿…è¦ãªå‡ºåŠ›ã«å¤‰æ›ã™ã‚‹é–¢æ•°ã§ã‚ã‚‹ã€‚é‡ã¿ä»˜ã‘ãƒ™ã‚¯ãƒˆãƒ« ã¯ãƒ©ãƒ™ãƒ«ä»˜ãè¨“ç·´ä¾‹ã§å¦ç¿’ã™ã‚‹ã“ã¨ã§å¤‰åŒ–ã—ã¦ã„ãã€‚f ã¯ã‚ã‚‹ã—ãã„å€¤ä»¥ä¸Šã®å€¤ã‚’ç¬¬ä¸€ã‚¯ãƒ©ã‚¹ã«åˆ†é¡žã—ã€ãã‚Œä»¥å¤–ã‚’ç¬¬äºŒã‚¯ãƒ©ã‚¹ã«åˆ†é¡žã™ã‚‹ã¨ã„ã£ãŸå˜ç´”ãªé–¢æ•°ã§ã‚ã‚‹ã“ã¨ãŒå¤šã„ï¼ˆäºŒé …åˆ†é¡žï¼‰ã€‚ã‚ˆã‚Šè¤‡é›‘ãª f ã¨ã—ã¦ã¯ã€ã‚ã‚‹é …ç›®ãŒã‚ã‚‹ã‚¯ãƒ©ã‚¹ã«å±žã™ã‚‹ç¢ºçŽ‡ã‚’ä¸Žãˆã‚‹ã‚‚ã®ãªã©ãŒã‚ã‚‹ã€‚ äºŒé …åˆ†é¡žå•é¡Œã¯ã€é«˜æ¬¡å…ƒã®å…¥åŠ›ç©ºé–“ã‚’è¶…å¹³é¢ã§åˆ†å‰²ã™ã‚‹æ“ä½œã¨ã—ã¦è¦–è¦šåŒ–ã§ãã‚‹ã€‚ãã®è¶…å¹³é¢ã®ä¸€æ–¹ã®å´ã«ã‚ã‚‹ç‚¹ã¯åˆ†é¡žã«ãŠã„ã¦ "yes" ã¨ã•ã‚Œ
seikenn 2011/05/19
LDA
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LDA è¿½è©¦(è¨“ç·´ãƒ‡ãƒ¼ã‚¿ã¨ãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã‚’åˆ†ã‘ãŸã‚‰) - æœ¨æ›œä¸è¶³
LDA ã®è©•ä¾¡çµæžœï¼‹Collapsed Variational Bayesian ã®åˆæœŸåŒ–ã«ãŠã‘ã‚‹å·¥å¤« - Mi manca qualche giovedi`? ã®ã‚³ãƒ¡ãƒ³ãƒˆæ¬„ã«ã¦ã€daichi ã•ã‚“ã«ã€Œãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã‚’ç”¨æ„ã—ã¦ã€ãã¡ã‚‰ã®perplexityã‚’é †æ¬¡è©•ä¾¡ã—ã¦ã¿ã‚‹ã¨ã©ã†ãªã‚‹ã§ã—ã‚‡ã†ã‹ã€‚LWLMç‰ã¨åŒæ§˜ã€ãã®å ´åˆã«ã¯ smart init ãŒä¸€ç•ªé«˜ã„ç¢ºçŽ‡ã‚’ä¸Žãˆã‚‹å¯èƒ½æ€§ãŒã‚ã‚‹ã‹ã‚‚çŸ¥ã‚Œã¾ã›ã‚“ã€ã¨ã‚¢ãƒ‰ãƒã‚¤ã‚¹ã‚’ã„ãŸã ã„ãŸã€‚å¤šè¬ã€‚ Î¸_d ãŒå¤§å¤‰ãã†ã€ã¨ã¤ã¶ã‚„ã„ã¦ãŸã‚‰åŒã˜ãã‚³ãƒ¡ãƒ³ãƒˆæ¬„ã«ã¦ yossy ã•ã‚“ã‹ã‚‰ã€ŒÎ¸_då‘¨ã‚Šã®å®Ÿè£…ãŒå°‘ã—é¢å€’ãªã›ã„ã‹ã€å„æ–‡æ›¸ã®90%ã®å˜èªžã§å¦ç¿’ã—ã¦æ®‹ã‚Š10%ã§è©•ä¾¡ã™ã‚‹ã“ã¨ãŒã‚ˆãè¡Œã‚ã‚Œã¾ã™ã€ã¨ã•ã‚‰ã«ã‚¢ãƒ‰ãƒã‚¤ã‚¹ã‚’ã„ãŸã ã„ãŸã€‚ã¾ãŸã¾ãŸå¤šè¬ã€‚ ã¨ã„ã†ã‚ã‘ã§è©¦ã—ã¦ã¿ãŸã€‚ https://github.com/shuyo/iir/blob/master/lda/lda_test
seikenn 2011/05/12
LDA
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http://blog.yuku-t.com/entry/20110508/1304860257
seikenn 2011/05/09
LDA
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[NLP] ç¬¬äº”å›žè‡ªç„¶è¨€èªžå‡¦ç†å‹‰å¼·ä¼šã§ç™ºè¡¨ã—ã¦ãã¾ã—ãŸ - tsubosakaã®æ—¥è¨˜
id:nokunoã•ã‚“ã®ä¸»å‚¬ã™ã‚‹è‡ªç„¶è¨€èªžå‡¦ç†å‹‰å¼·ä¼šã§ã€Infer.NETã‚’ä½¿ã£ã¦LDAã‚’å®Ÿè£…ã—ã¦ã¿ãŸã¨ã„ã†ã‚¿ã‚¤ãƒˆãƒ«ã§ç™ºè¡¨ã—ã¦ãã¾ã—ãŸã€‚ Infer.NETã¯MicrosoftãŒå…¬é–‹ã—ã¦ã„ã‚‹ã‚°ãƒ©ãƒ•ã‚£ã‚«ãƒ«ãƒ¢ãƒ‡ãƒ«ä¸Šã§ãƒ™ã‚¤ã‚ºæŽ¨å®šã‚’è¡Œã†ãŸã‚ã®ãƒ•ãƒ¬ãƒ¼ãƒ ãƒ¯ãƒ¼ã‚¯ã§ã™ã€‚ã“ã®ã‚ˆã†ãªã‚‚ã®ã‚’ä½¿ã†ã“ã¨ã«ã‚ˆã‚Šã€å…·ä½“çš„ãªæŽ¨è«–ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã®å°Žå‡ºã‚’äººãŒè¡Œã†ã“ã¨ãªãã€ç”Ÿæˆãƒ¢ãƒ‡ãƒ«ã‚’è¨˜è¿°ã™ã‚‹ã ã‘ã§äº‹å¾Œåˆ†å¸ƒã®æŽ¨è«–ãŒå¯èƒ½ã«ãªã‚Šã€ç°¡å˜ã«ç¢ºçŽ‡ãƒ¢ãƒ‡ãƒ«ã‚’å•é¡Œã«åˆã‚ã›ã¦å®šç¾©ã™ã‚‹ã¨ã„ã†ã“ã¨ãŒè¡Œãˆã‚‹ã‚ˆã†ã«ãªã‚‹ã¨ã„ã„ãªã¨æ€ã£ã¦ã€ä»Šå›žç´¹ä»‹ã—ã¾ã—ãŸã€‚ Infer.NETã‚’ä½¿ã£ã¦LDAã‚’å®Ÿè£…ã—ã¦ã¿ãŸ View more presentations from tsubosaka å‚è€ƒæ–‡çŒ® Infer.NETã‚’ä½¿ã†ä¸Šã§å‚è€ƒã«ãªã‚‹ã‹ã¨æ€ã‚ã‚Œã‚‹æ›¸ç±ã‚’ã‚ã’ã¦ãŠãã¾ã™ã€‚ ãƒ‘ã‚¿ãƒ¼ãƒ³èªè˜ã¨æ©Ÿæ¢°å¦ç¿’ ä¸Š - ãƒ™ã‚¤ã‚ºç†è«–ã«ã‚ˆã‚‹çµ±è¨ˆçš„äºˆæ¸¬ ä½œè€…: C. M.ãƒ“ã‚·ãƒ§ãƒƒãƒ—,å…ƒç”°æµ©
seikenn 2011/04/28
LDA
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lda, a Latent Dirichlet Allocation package
lda, a Latent Dirichlet Allocation package. Daichi Mochihashi NTT Communication Science Laboratories $Id: index.html,v 1.3 2004/12/04 12:47:35 daiti-m Exp $ Overview lda is a Latent Dirichlet Allocation (Blei et al., 2001) package written both in MATLAB and C (command line interface). This package provides only a standard variational Bayes estimation that was first proposed, but has a simple textu
seikenn 2011/04/22
LDA
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ãƒ‡ã‚£ãƒªã‚¯ãƒ¬åˆ†å¸ƒã®ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ãŒ0ã®ã¨ã - æœ¨æ›œä¸è¶³
ãƒ‡ã‚£ãƒªã‚¯ãƒ¬åˆ†å¸ƒã®ãƒã‚¤ãƒ‘ãƒ¼ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã¯ a_i > 0 ãªã®ã ã‘ã©ã€a_i = 0 ã®å ´åˆã¯ãã®è¦ç´ ãŒç¸®é€€ã—ãŸã¨è€ƒãˆã‚‹ã“ã¨ãŒå‡ºæ¥ã‚‹ã‚ˆã€œçš„ãªã“ã¨ã‚’ Furguson ã®è«–æ–‡ã§è¦‹ãŸè¦šãˆãŒã‚ã£ãŸã®ã§ã€ç¤¾å†…ã§ã® PRML å‹‰å¼·ä¼šã§ãã‚Œã‚’ã¡ã‚‰ã£ã¨è¨€ã£ã¦ã¿ãŸã‚‰ã€ã¡ã‚ƒã‚“ã¨è¨¼æ˜Žã—ã¦ãã‚Œãªã„ã¨ã€œã€ã¨è¥¿å°¾ã•ã‚“ã«ãƒ•ãƒ«ãƒœãƒƒã‚³ã«ã•ã‚ŒãŸã€‚ ã¨ã„ã†ã‚ã‘ã§ã€PRML ã®ç¯„å›²ã§ã¡ã‚‡ã£ã¨ã¾ã˜ã‚ã«è€ƒãˆã¦ã¿ãŸã€‚ ã¾ãšæº–å‚™ã¨ã—ã¦ x = cy ã¨å¤‰æ•°å¤‰æ›ã™ã‚‹ã“ã¨ã§ä»¥ä¸‹ã®å¼ã‚’ç¤ºã—ã¦ãŠãã€‚ãŸã ã— B(a,b) ã¯Î²é–¢æ•°ã€‚ K æ¬¡ã®ãƒ‡ã‚£ãƒªã‚¯ãƒ¬åˆ†å¸ƒã‚’è€ƒãˆã‚‹(Z ã¯æ£è¦åŒ–å®šæ•°) ãŸã ã— ãªã®ã§ã€ x_K ã‚’æ¶ˆã™ã¨ ã“ã‚Œã‚’ x_{K-1} ã§å‘¨è¾ºåŒ–ã™ã‚‹ã€‚ ã“ã‚Œã‚ˆã‚Š ãŒ ã‚’ãƒã‚¤ãƒ‘ãƒ¼ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã¨ã™ã‚‹ (K-1) æ¬¡ã®ãƒ‡ã‚£ãƒªã‚¯ãƒ¬åˆ†å¸ƒã«å¾“ã†ã“ã¨ãŒã‚ã‹ã‚‹ã€‚ åŒæ§˜ã«ï¼‘ã¤ãšã¤å¤‰æ•°ã‚’æ¸›ã‚‰ã—ã¦ã„ãã“ã¨ã§ã€ å„ x_k ã¯Î²åˆ†å¸ƒ ã«å¾“ã†ã“ã¨ãŒè¨€ãˆã‚‹ã€‚ æ¬¡ã«ã€Î²åˆ†å¸ƒ
seikenn 2011/03/04
LDA
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Latent Dirichlet Allocations ã® Python å®Ÿè£… - æœ¨æ›œä¸è¶³
LDA ã¨ã¯ "Latent Dirichlet Allocation"ã€‚æ–‡æ›¸ä¸ã®å˜èªžã®ã€Œãƒˆãƒ”ãƒƒã‚¯ã€ã‚’ç¢ºçŽ‡çš„ã«æ±‚ã‚ã‚‹è¨€èªžãƒ¢ãƒ‡ãƒ«ã€‚ ã€Œæ½œåœ¨çš„ãƒ‡ã‚£ãƒªã‚¯ãƒ¬é…åˆ†æ³•ã€ã¨è¨³ã•ã‚Œã¦ã„ã‚‹ã“ã¨ã‚‚ã‚ã‚‹ãŒã€ãã®åå‰ã ã¨ã€Œãã‚Œã£ã¦ãªã‚“ã ã£ã‘ï¼Ÿã€ã¨ã„ã†äººã®ã»ã†ãŒå¤šãã†ï½—ã€‚ å„å˜èªžãŒã€Œéš ã‚Œãƒˆãƒ”ãƒƒã‚¯ã€(è©±é¡Œã€ã‚«ãƒ†ã‚´ãƒªãƒ¼)ã‹ã‚‰ç”Ÿæˆã•ã‚Œã¦ã„ã‚‹ã€ã¨æƒ³å®šã—ã¦ã€ãã®ãƒˆãƒ”ãƒƒã‚¯ã‚’æ–‡æ›¸é›†åˆã‹ã‚‰æ•™å¸«ç„¡ã—ã§æŽ¨å®šã™ã‚‹ã“ã¨ãŒã§ãã‚‹ã€‚ç‰¹å¾´ã¯ã€æžœç‰©ã® apple ã¨éŸ³æ¥½ã® apple ã¨ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿é–¢é€£ã® apple ã‚’åŒºåˆ¥ã™ã‚‹ã“ã¨ãŒå‡ºæ¥ã‚‹(ã“ã¨ãŒæœŸå¾…ã•ã‚Œã‚‹)ã¨ã„ã†ç‚¹ã€‚ãã®ãŸã‚ã«ã€ã©ã®ãƒˆãƒ”ãƒƒã‚¯ã‚’ç”Ÿæˆã—ã‚„ã™ã„ã‹ã¨ã„ã†åˆ†å¸ƒã‚’å„æ–‡ç« ã‚‚æŒã¤ã€‚ç´°ã‹ã„è©±ã¯ç•¥ã€‚ çµæžœã®è¦‹æ–¹ã¨ã—ã¦ã¯ã€å®šé‡çš„ã«ã¯ãƒ‘ãƒ¼ãƒ—ãƒ¬ã‚ã‚·ãƒ†ã‚£ã‚’è¦‹ã‚‹ã—(ä¸€èˆ¬ã«å°ã•ã„ã»ã©ã„ã„)ã€å®šæ€§çš„ã«ã¯å„ãƒˆãƒ”ãƒƒã‚¯ãŒã©ã®ã‚ˆã†ãªå˜èªžã‚’ç”Ÿæˆã™ã‚‹ã‹ã€ãã®ç¢ºçŽ‡ä¸Šä½ã®ã‚‚ã®ã‚’è¦‹ã¦ãµã‚€ãµã‚€ã™ã‚‹ã€‚ã“ã®ã€Œå„ãƒˆãƒ”ãƒƒã‚¯ãŒç”Ÿæˆã™ã‚‹å˜èªžã€
seikenn 2011/02/28
LDA
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Latent Dirichlet Allocations(LDA) ã®å®Ÿè£…ã«ã¤ã„ã¦ - æœ¨æ›œä¸è¶³
æ˜¨æ—¥ã® "Latent Dirichlet Allocations in Python" ã®ç¶šãã§å®Ÿé¨“çµæžœã‚’è¼‰ã›ã‚ˆã†ã‹ã¨æ€ã£ãŸã‘ã©ã€å…ˆã«ã‚„ã£ã±ã‚Šã‚‚ã†ã¡ã‚‡ã£ã¨ LDA ã‚’èª¬æ˜Žã—ã¦ãŠã“ã†ã€‚ LDA ã®åˆå‡ºã¯ [Blei+ 2003] Latent Dirichlet Allocation ã€‚ ãŸã ã— [Blei+ 2003] ã§ "LDA" ã¨ã—ã¦ã„ã‚‹ã®ã¯ãƒˆãƒ”ãƒƒã‚¯-å˜èªžåˆ†å¸ƒãŒãŸã ã®å¤šé …åˆ†å¸ƒ(äº‹å‰åˆ†å¸ƒç„¡ã—)ã®ã‚‚ã®ã€‚"LDA" ã¨ã—ã¦ã‚ˆãç›®ã«ã™ã‚‹ãƒˆãƒ”ãƒƒã‚¯-å˜èªžå¤šé …åˆ†å¸ƒã«ãƒ‡ã‚£ãƒªã‚¯ãƒ¬äº‹å‰åˆ†å¸ƒãŒå…¥ã£ãŸã‚‚ã®ã¯ "Smoothed LDA" ã¨ã—ã¦è¨˜è¼‰ã•ã‚Œã¦ã„ã‚‹(ç¢ºã‹ã«Î²ã§ã‚¹ãƒ ãƒ¼ã‚¸ãƒ³ã‚°ã—ã¦ã„ã‚‹ã®ã¨ç‰ä¾¡)ã€‚ ä»Šå›žå®Ÿè£…ã—ãŸ LDA ã‚‚å¾Œè€…ã® "Smoothed LDA"ã€‚ ãã® LDA ã¯ã“ã‚“ãªæ„Ÿã˜ã€‚Î±ã¨Î²ã¯ãƒã‚¤ãƒ‘ãƒ¼ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã ã‹ã‚‰ã€ãƒãƒ“é»’ä¸¸ã§æ›¸ã„ã¦æ¬²ã—ã„ã‚“ã ã‘ã©ãã€‚ (å›³ã¯ Wikipedia-en ã® LD
seikenn 2011/02/28
LDA
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