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RjpWiki - RjpWiki
RjpWiki ã¯ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã®çµ±è¨ˆè§£æžã‚·ã‚¹ãƒ†ãƒ R ã«é–¢ã™ã‚‹æƒ…å ±äº¤æ›ã‚’ç›®çš„ã¨ã—ãŸ Wiki ã§ã™RjpWiki ã¯ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã®çµ±è¨ˆè§£æžã‚·ã‚¹ãƒ†ãƒ ã€ŠRã€‹ ã«é–¢ã™ã‚‹æƒ…å ±äº¤æ›ã‚’ç›®çš„ã¨ã—ãŸ Wiki ã§ã™ â€ ã©ãªãŸã§ã‚‚è‡ªç”±ã«ãƒšãƒ¼ã‚¸ã‚’è¿½åŠ ãƒ»ç·¨é›†ã§ãã¾ã™ï¼Ž (åˆã‚ã¦æŠ•ç¨¿ãƒ»æ—¢å˜è¨˜äº‹ã¸ã®è¿½åŠ ãƒ»ä¿®æ£ã‚’è¡Œãªã†æ–¹ã¯ã“ã®ãƒšãƒ¼ã‚¸æœ«ã®æ³¨æ„*1ã‚’å¾¡è¦§ä¸‹ã•ã„) ãƒšãƒ¼ã‚¸ã¸ã®ãƒ•ã‚¡ã‚¤ãƒ«æ·»ä»˜ã«ã¤ã„ã¦ã¯ã€ç”»åƒãƒ•ã‚¡ã‚¤ãƒ«ã®ã¿ãƒ‘ã‚¹ãƒ¯ãƒ¼ãƒ‰ãªã—ã§å¯èƒ½ã¨ã—ã¦ã‚ã‚Šã¾ã™(ãƒšãƒ¼ã‚¸ä¸Šéƒ¨ã€Œç”»åƒæ·»ä»˜ã€ã‚ˆã‚Š)ã€‚ãã®ä»–ã®ãƒ•ã‚¡ã‚¤ãƒ«ã®æ·»ä»˜ã¯ãƒ‘ã‚¹ãƒ¯ãƒ¼ãƒ‰ã‚’å…¥åŠ›ã™ã‚‹ã“ã¨ã§å¯èƒ½ã§ã™(ãƒšãƒ¼ã‚¸ä¸Šéƒ¨ã€Œãƒ•ã‚¡ã‚¤ãƒ«æ·»ä»˜ã€ã‚ˆã‚Š)ã€‚ç¾åœ¨ã®ãƒ‘ã‚¹ãƒ¯ãƒ¼ãƒ‰ã¯, Rã§ã® round(qt(0.2,df=8),3) ã®å®Ÿè¡Œçµæžœã§ã™ã€‚ ã‚¹ãƒ‘ãƒ æ›¸ãè¾¼ã¿ã«å¯¾å‡¦ã™ã‚‹ãŸã‚ã€æ›¸ãè¾¼ã¿ç³»ã®å‡¦ç†ã«å¯¾ã—ã¦ãƒ‘ã‚¹ãƒ¯ãƒ¼ãƒ‰ã‚’è¨ã‘ã¾ã—ãŸã€‚ãƒ¦ãƒ¼ã‚¶åã®æ¬„ã«ã¯ï¼ŒRã§ round(qt(0.2,df=8),3) ã‚’å®Ÿè¡Œ
tomity 2011/01/26
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JIN'S PAGE - R
Rã€Rè¨€èªžã€Rç’°å¢ƒãƒ»ãƒ»ãƒ»ãƒ»ãƒ»ãƒ» Rã®ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã¨ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ« ãƒªãƒ³ã‚¯é›† é¡Œå Chap_01 ãƒ‡ãƒ¼ã‚¿è§£æžãƒ»ãƒžã‚¤ãƒ‹ãƒ³ã‚°ã¨Rè¨€èªž Chap_0ï¼’ Rã§ã®ãƒ‡ãƒ¼ã‚¿ã®å…¥å‡ºåŠ› Chap_03 Rã§ã®ãƒ‡ãƒ¼ã‚¿ã®ç·¨é›†ã¨æ¼”ç®— Chap_04 Rã¨åŸºæœ¬çµ±è¨ˆé‡ Chap_05 Rã§ã®é–¢æ•°ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆ Chap_06 Rã§ã®ãƒ‡ãƒ¼ã‚¿ã®è¦–è¦šåŒ–(1) Chap_07 Rã§ã®ãƒ‡ãƒ¼ã‚¿ã®è¦–è¦šåŒ–(2) Chap_08 Rã§ã®ãƒ‡ãƒ¼ã‚¿ã®è¦–è¦šåŒ–(3) Chap_09 GGobiã¨ãƒ‡ãƒ¼ã‚¿ã®è¦–è¦šåŒ–(Rgobi) Chap_10 Rã¨ç¢ºçŽ‡åˆ†å¸ƒ Chap_11 Rã¨æŽ¨å®š Chap_12 Rã¨æ¤œå®š Chap_13 Rã¨åˆ†æ•£åˆ†æž Chap_14 Rã¨å›žå¸°åˆ†æž Chap_15 Rã¨é‡å›žå¸°åˆ†æž Chap_16 Rã¨ä¸€èˆ¬åŒ–ç·šå½¢ãƒ¢ãƒ‡ãƒ« Chap_17 Rã¨éžç·šå½¢ãƒ¢ãƒ‡ãƒ« Chap_18 Rã¨åˆ¤åˆ¥åˆ†æž Chap_19 Rã¨æ¨¹æœ¨ãƒ¢ãƒ‡ãƒ« Chap_20 WEK
tomity 2011/01/26
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Python logistic regression (with L2 regularization) | This Number Crunching Life
Randomness in the world with a smattering of other randomness Logistic Regression Logistic regression is used for binary classification probl ems -- where you have some examples that are "on" and other examples that are "off." You get as input a training set which has some examples of each class along with a label saying whether each example is "on" or "off". The goal is to learn a model from the t
tomity 2010/08/03
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[Think IT] ã‚µãƒ¼ãƒãŒé‡ã„ã£ã¦ã©ã†ã„ã†ã“ã¨? (1/3)
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tomity 2010/06/24
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Netflix - Watch TV Shows Online, Watch Movies Online
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tomity 2009/04/21
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Link Analysis and Related Topics - Home
2008å¹´åº¦ å…ˆç«¯æƒ…å ±ç§‘å¦ç‰¹è«– II & IV ãƒªãƒ³ã‚¯è§£æžã¨å‘¨è¾ºã®è©±é¡Œ æ‹…å½“ æ–°ä¿ ä» [email protected]aist.jp æ—¥æ™‚ 2008/11/10, 11/17, 12/1, 12/8 (å…¨ 4 å›ž) - 4é™ 15:10-16:40 å ´æ‰€ æƒ…å ±æ£Ÿ L3 è¬›ç¾©å®¤ ãƒªãƒ³ã‚¯è§£æžã¯, ã‚°ãƒ©ãƒ• (ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯) ãƒ‡ãƒ¼ã‚¿ã®æ§‹é€ ã‹ã‚‰æœ‰ç”¨ãªæƒ…å ±ã‚’æŠ½å‡ºã™ã‚‹ãŸã‚ã®, ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°ã®ä¸€ç ”ç©¶åˆ†é‡Žã§ã™. ã“ã®è¬›ç¾©ã§ã¯ã¾ãš, ãƒªãƒ³ã‚¯è§£æžãŒå–ã‚Šæ‰±ã† 2 ç¨®é¡žã®å°ºåº¦ (é‡è¦åº¦ã¨é–¢é€£åº¦) ã«ã¤ã„ã¦è¿°ã¹, ãã‚Œãžã‚Œã®ä»£è¡¨çš„ãªè¨ˆç®—æ‰‹æ³•ã‚’ç´¹ä»‹ã—ã¾ã™. å¾ŒåŠã§ã¯, è¿‘å¹´æ©Ÿæ¢°å¦ç¿’åˆ†é‡Žã§ç››ã‚“ã«ç ”ç©¶ã•ã‚Œã¦ã„ã‚‹ã‚«ãƒ¼ãƒãƒ«ã®ã†ã¡, ã‚°ãƒ©ãƒ•ä¸Šã®ç¯€ç‚¹ã«å¯¾ã—ã¦å®šç¾©ã•ã‚ŒãŸã‚«ãƒ¼ãƒãƒ« (ã‚°ãƒ©ãƒ•ã‚«ãƒ¼ãƒãƒ«) ã¨, ãã®ãƒªãƒ³ã‚¯è§£æžã¸ã®å¿œç”¨ã«ã¤ã„ã¦ç´¹ä»‹ã—ã¾ã™. ç¬¬1å›ž 11æœˆ10æ—¥ ã‚¹ãƒ©ã‚¤ãƒ‰ ç¬¬2å›ž 11æœˆ17æ—¥ ã‚¹ãƒ©ã‚¤ãƒ‰ ç¬¬3å›ž 12æœˆ1æ—¥
tomity 2009/03/01
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Paul Komarek's Logistic Regression Page
tomity 2009/01/28
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Statistical Language Modeling Toolkit
Statistical Language Modeling Toolkit The CMU-Cambridge Statistical Language Modeling toolkit is a suite of UNIX software tools to facilitate the construction and testing of statistical language models. Version 1 was written by Roni Rosenfeld at Carnegie Mellon University. The toolkit has now been rewritten by Philip Clarkson and Roni Rosenfeld, and now provides increased functionality and efficie
tomity 2008/08/06
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