Signed distance function - Revision history

en>Billinghurst: Disambiguate Hessian to Hessian matrix using popups

2014-09-04T11:41:26Z

Disambiguate Hessian to Hessian matrix using popups

← Older revision		Revision as of 13:41, 4 September 2014
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	~~{{One source\|date=August 2010}}~~		Hi there. Let me start by introducing the author, her name is Sophia. North Carolina is where we've been residing for years and will never move. Credit authorising is how he makes cash. To perform lacross is the thing I love most of all.<br><br>my blog post - psychics online ([http://www.seekavideo.com/playlist/2199/video/ click the following page])
	~~In [[mathematics]]~~ the '''signal-to-noise statistic''' [[distance]] between two [[vector (geometric)\|vectors]] ''a'' and ''b'' with [[Arithmetic Mean\|mean]] values <math>\mu _a</math> and <math>\mu _b</math> and [[standard deviation]] <math>\sigma _a</math> and <math>\sigma _b</math> respectively is:

	~~:<math>D_{sn} = {(\mu _a - \mu _b) \over (\sigma _a + \sigma _b)}</math>~~

	In the case of Gaussian-distributed data and unbiased class distributions, this statistic can be related to classification accuracy given an ideal linear discrimination, and a decision boundary can be derived.~~<ref>Auffarth, B., Lopez, M., Cerquides, J. (2010). Comparison of redundancy and relevance measures~~ for ~~feature selection in tissue classification of CT images. Advances in Data Mining. Applications~~ and ~~Theoretical Aspects~~. p. ~~248--262. Springer~~. ~~http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.170.1528~~<~~/ref~~>

	This distance is frequently used to identify vectors that have significant difference. One usage is in [[bioinformatics]] to locate [[genes]] that are differential [[Gene expression\|expressed]] on [[microarray]] experiments.<~~ref~~>~~Pomeroy, S.L. et al.~~ [http://www.~~broad.mit~~.~~edu~~/~~mpr~~/~~CNS~~/ ~~Gene Expression-Based Classification and Outcome Prediction of Central Nervous System Embryonal Tumors]. Nature 415, 436–442.<~~/~~ref>~~

	~~==See also==~~
	*[[Distance]]
	*[[Uniform norm]]
	*[[Manhattan distance]]
	*[[Signal-to-noise ratio]]
	*[[Signal to noise ratio (imaging)]]

	~~==Notes==~~
	~~{{Reflist}}~~

	~~{{DEFAULTSORT:Signal-To-Noise Statistic}}~~
	~~[[Category:Statistical distance measures]]~~
	~~[[Category:Statistical ratios]]~~


	~~{{Statistics-stub}}~~

178.24.212.116 at 12:01, 30 June 2013

2013-06-30T12:01:17Z

← Older revision		Revision as of 14:01, 30 June 2013
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	~~Greetings! I am Myrtle Shroyer. South Dakota~~ is ~~her beginning place but she requirements~~ to ~~move simply because~~ of ~~her family members~~. ~~To do aerobics~~ is ~~a factor~~ that ~~I'm completely addicted to~~. ~~Hiring~~ is ~~her day occupation now but she's always wanted her own company~~.<br>~~<br>my web site~~ [http://www.~~buzzbit~~.~~net~~/~~blog~~/~~333162 std home test~~]		{{One source\|date=August 2010}}
			In [[mathematics]] the '''signal-to-noise statistic''' [[distance]] between two [[vector (geometric)\|vectors]] ''a'' and ''b'' with [[Arithmetic Mean\|mean]] values <math>\mu _a</math> and <math>\mu _b</math> and [[standard deviation]] <math>\sigma _a</math> and <math>\sigma _b</math> respectively is:

			:<math>D_{sn} = {(\mu _a - \mu _b) \over (\sigma _a + \sigma _b)}</math>

			In the case of Gaussian-distributed data and unbiased class distributions, this statistic can be related to classification accuracy given an ideal linear discrimination, and a decision boundary can be derived.<ref>Auffarth, B., Lopez, M., Cerquides, J. (2010). Comparison of redundancy and relevance measures for feature selection in tissue classification of CT images. Advances in Data Mining. Applications and Theoretical Aspects. p. 248--262. Springer. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.170.1528</ref>

			This distance is frequently used to identify vectors that have significant difference. One usage is in [[bioinformatics]] to locate [[genes]] that are differential [[Gene expression\|expressed]] on [[microarray]] experiments.<ref>Pomeroy, S.L. et al. [http://www.broad.mit.edu/mpr/CNS/ Gene Expression-Based Classification and Outcome Prediction of Central Nervous System Embryonal Tumors]. Nature 415, 436–442.</ref>

			==See also==
			*[[Distance]]
			*[[Uniform norm]]
			*[[Manhattan distance]]
			*[[Signal-to-noise ratio]]
			*[[Signal to noise ratio (imaging)]]

			==Notes==
			{{Reflist}}

			{{DEFAULTSORT:Signal-To-Noise Statistic}}
			[[Category:Statistical distance measures]]
			[[Category:Statistical ratios]]


			{{Statistics-stub}}

128.40.56.75: Clearly the definition of f given in the article means that \nabla f is the inward pointing normal

2012-08-06T16:57:05Z

Clearly the definition of f given in the article means that \nabla f is the inward pointing normal

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