Electron temperature - Revision history

en>Brianhe: ce first-person tone

2015-01-04T05:22:57Z

ce first-person tone

← Older revision		Revision as of 07:22, 4 January 2015
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	~~Royal Votaw is~~ my ~~title but I never really favored that~~ name. ~~His day job~~ is a cashier ~~and his salary has been really fulfilling~~. ~~Her husband and her selected~~ to ~~reside~~ in ~~Alabama~~. ~~The factor I adore most flower arranging and now~~ I ~~have time to consider on new things~~.<br><br>~~Here is~~ my ~~webpage: extended car warranty (~~[http://~~Www~~.~~Classicguides.com~~/~~automotive~~/~~extended-vehicle-warranty-plans~~/ ~~Click On this site~~])		Hello! Let me start by saying my name - Ron Stephenson. She is presently a cashier but quickly she'll be on her personal. Some time in the past he chose to live in Kansas. To play croquet is some thing that I've done for many years.<br><br>Have a look at my blog post ... [http://Titon.net/UserProfile/tabid/43/userId/160343/Default.aspx Titon.net]

en>Ntaylor5 at 09:03, 28 February 2014

2014-02-28T09:03:55Z

← Older revision		Revision as of 11:03, 28 February 2014
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	~~The '''transferable belief model (TBM)'''~~ is ~~an elaboration on the [[Dempster–Shafer theory]] of evidence.~~		Royal Votaw is my title but I never really favored that name. His day job is a cashier and his salary has been really fulfilling. Her husband and her selected to reside in Alabama. The factor I adore most flower arranging and now I have time to consider on new things.<br><br>Here is my webpage: extended car warranty ([http://Www.Classicguides.com/automotive/extended-vehicle-warranty-plans/ Click On this site])
	~~==Context==~~
	Consider the following classical problem of [[information fusion]]. A patient has an illness that can be caused by three different factors ''A'', ''B'' and ''C''. Doctor 1 says that the patient's illness is very likely to be caused by A (very likely, meaning probability ''p'' = 0.95), but ~~''B'' is also possible but not likely (''p'' = 0.05). Doctor 2 says~~ that ~~the cause is very likely ''C'' (''p'' = 0~~.~~95), but ''B''~~ is ~~also possible but not likely (''p'' = 0.05). How is one to make one's own opinion from this ?~~

	~~Bayesian updating the first opinion with the second (or the other way round) implies certainty that the cause is ''B''. [[Dempster's rule of combination]] lead to the same result~~. ~~This can be seen as [[paradox\|paradoxical]], since although the two doctors point at different causes, ''A''~~ and ~~''C'', they both agree that ''B'' is not likely. (For this reason the standard Bayesian approach is~~ to ~~adopt [[Cromwell's rule]] and avoid the use of 0 or 1 as probabilities~~.)

	The transferable belief model (TBM) is an elaboration on the [[Dempster–Shafer theory]] of evidence developed by Dr. Philippe Smets, based on the intuition that in the situation above, the result should allocate most ~~of the belief weight~~ to the empty set (i.e. neither ''A'', ''B'', nor ''C''). Technically, this would be done by using the TBM conjunction rule for non-interactive sources of information, which is the same as [[Dempster's rule of combination]] without renormalization.

	~~While most other theories adhere to the axiom ''the probability (or belief mass) of the empty set is always zero'', there is another intuitive reason to drop this axiom: the open-world assumption~~. It applies when the frame of reference is not exhaustive, so there are reason to believe that an event not described in this frame of reference will occur. For example, when tossing a coin one usually assumes that Head or Tail will occur, so that <~~math~~>~~\scriptstyle \Pr(\mathrm{Head})+\Pr(\mathrm{Tail})=1~~<~~/math~~>~~. The open-world assumption is that the coin can be stolen in mid-air, disappear, break apart or otherwise fall sideway so that neither Head nor Tail occurs, so that the power set of {Head,Tail}~~ is ~~considered and there is a decompostion of the overall probability (i.e. 1) of the following form:~~
	~~:<math> \Pr(\varnothing)+\Pr(\mathrm{Head})+\Pr(\mathrm{Tail})+\Pr(\mathrm{Head,Tail}) =1.</math>~~

	~~==See also==~~

	* [[Dempster–Shafer theory]]

	~~{{No footnotes\|date=June 2010}}~~

	~~==References==~~
	*Smets Ph. (1988) "Belief function". In: ~~''Non Standard Logics for Automated Reasoning'', ed. Smets Ph., Mamdani A, Dubois D. and Prade H. Academic Press, London~~
	*Smets Ph. (1990) "The combination of evidence in the transferable belief model", ''IEEE Pattern Analysis and Machine Intelligence'', 12, 447–458
	*Smets Ph. (~~1993) "An axiomatic justification for the use of belief function to quantify beliefs", IJCAI'93 (Inter. Joint Conf. on AI), Chambery, 598–603~~
	*Smets Ph. and Kennes R. (1994) "The transferable belief model", ''Artificial Intelligence'', 66,191–234
	*Smets Ph. and Kruse R. (1995) "The transferable belief model for belief representation" In: Smets and Motro A. (eds.) ''Uncertainty Management in Information Systems: from Needs to solutions''. Kluwer, Boston
	*Ramasso, E., Rombaut, M., Pellerin D. (2007) [http://~~hal~~.~~archives-ouvertes~~.fr/~~docs~~/~~00/34/85/77/PDF/ramasso_rombaut_pellerin_escqaru07_CRHMM.pdf "Forward~~-~~Backward~~-~~Viterbi procedures in the Transferable Belief Model for state sequence analysis using belief functions"], ''ECSQARU, Hammamet : Tunisie (2007)''.~~
	*Touil, K., Zribi, M., Benjelloun, M. (2007) [http:/~~/iospress.metapress.com/content/FW6KLYTMAB49FNXH "Application of transferable belief model to navigation system"~~]~~, ''Integrated Computer-Aided Engineering'', 14 (1~~)~~, 93–105~~

	~~==External links==~~
	*[http://iridia.ulb.ac.be/Projects/trans.html ''The Transferable Belief Model'']
	*[http://iridia.ulb.ac.be/~psmets/AABPapers.html ''Publications on TBM'']
	*[http://iridia.ulb.ac.be/~psmets/#G ''Software for TBM in Matlab'']

	~~[[Category:Logic]]~~
	~~[[Category:Statistical inference]]~~

82.13.79.190: Fixed spelling mistake - 'Entroopy' instead of 'Entropy'

2013-12-26T14:08:08Z

Fixed spelling mistake - 'Entroopy' instead of 'Entropy'

← Older revision		Revision as of 16:08, 26 December 2013
Line 1:		Line 1:
	~~Hi there~~. ~~My title~~ is ~~Garland even though it~~ is not the ~~name on my beginning certification~~. ~~Interviewing~~ is ~~what she does~~ but ~~quickly she~~'ll be on ~~her own~~. ~~One~~ of ~~my preferred hobbies~~ is ~~tenting and now I~~'~~m trying~~ to ~~earn cash with it~~. ~~Delaware~~ is ~~our birth place~~.<br><br>~~my page~~ ... [http://~~Freebusinesscollege~~.~~com~~//~~read_blog~~/~~198199~~/~~great~~-~~ideas~~-~~about~~-~~auto-repair-that-anyone-can-use freebusinesscollege~~.~~com~~]		The '''transferable belief model (TBM)''' is an elaboration on the [[Dempster–Shafer theory]] of evidence.
			==Context==
			Consider the following classical problem of [[information fusion]]. A patient has an illness that can be caused by three different factors ''A'', ''B'' and ''C''. Doctor 1 says that the patient's illness is very likely to be caused by A (very likely, meaning probability ''p'' = 0.95), but ''B'' is also possible but not likely (''p'' = 0.05). Doctor 2 says that the cause is very likely ''C'' (''p'' = 0.95), but ''B'' is also possible but not likely (''p'' = 0.05). How is one to make one's own opinion from this ?

			Bayesian updating the first opinion with the second (or the other way round) implies certainty that the cause is ''B''. [[Dempster's rule of combination]] lead to the same result. This can be seen as [[paradox\|paradoxical]], since although the two doctors point at different causes, ''A'' and ''C'', they both agree that ''B'' is not likely. (For this reason the standard Bayesian approach is to adopt [[Cromwell's rule]] and avoid the use of 0 or 1 as probabilities.)

			The transferable belief model (TBM) is an elaboration on the [[Dempster–Shafer theory]] of evidence developed by Dr. Philippe Smets, based on the intuition that in the situation above, the result should allocate most of the belief weight to the empty set (i.e. neither ''A'', ''B'', nor ''C''). Technically, this would be done by using the TBM conjunction rule for non-interactive sources of information, which is the same as [[Dempster's rule of combination]] without renormalization.

			While most other theories adhere to the axiom ''the probability (or belief mass) of the empty set is always zero'', there is another intuitive reason to drop this axiom: the open-world assumption. It applies when the frame of reference is not exhaustive, so there are reason to believe that an event not described in this frame of reference will occur. For example, when tossing a coin one usually assumes that Head or Tail will occur, so that <math>\scriptstyle \Pr(\mathrm{Head})+\Pr(\mathrm{Tail})=1</math>. The open-world assumption is that the coin can be stolen in mid-air, disappear, break apart or otherwise fall sideway so that neither Head nor Tail occurs, so that the power set of {Head,Tail} is considered and there is a decompostion of the overall probability (i.e. 1) of the following form:
			:<math> \Pr(\varnothing)+\Pr(\mathrm{Head})+\Pr(\mathrm{Tail})+\Pr(\mathrm{Head,Tail}) =1.</math>

			==See also==

			* [[Dempster–Shafer theory]]

			{{No footnotes\|date=June 2010}}

			==References==
			*Smets Ph. (1988) "Belief function". In: ''Non Standard Logics for Automated Reasoning'', ed. Smets Ph., Mamdani A, Dubois D. and Prade H. Academic Press, London
			*Smets Ph. (1990) "The combination of evidence in the transferable belief model", ''IEEE Pattern Analysis and Machine Intelligence'', 12, 447–458
			*Smets Ph. (1993) "An axiomatic justification for the use of belief function to quantify beliefs", IJCAI'93 (Inter. Joint Conf. on AI), Chambery, 598–603
			*Smets Ph. and Kennes R. (1994) "The transferable belief model", ''Artificial Intelligence'', 66,191–234
			*Smets Ph. and Kruse R. (1995) "The transferable belief model for belief representation" In: Smets and Motro A. (eds.) ''Uncertainty Management in Information Systems: from Needs to solutions''. Kluwer, Boston
			*Ramasso, E., Rombaut, M., Pellerin D. (2007) [http://hal.archives-ouvertes.fr/docs/00/34/85/77/PDF/ramasso_rombaut_pellerin_escqaru07_CRHMM.pdf "Forward-Backward-Viterbi procedures in the Transferable Belief Model for state sequence analysis using belief functions"], ''ECSQARU, Hammamet : Tunisie (2007)''.
			*Touil, K., Zribi, M., Benjelloun, M. (2007) [http://iospress.metapress.com/content/FW6KLYTMAB49FNXH "Application of transferable belief model to navigation system"], ''Integrated Computer-Aided Engineering'', 14 (1), 93–105

			==External links==
			*[http://iridia.ulb.ac.be/Projects/trans.html ''The Transferable Belief Model'']
			*[http://iridia.ulb.ac.be/~psmets/AABPapers.html ''Publications on TBM'']
			*[http://iridia.ulb.ac.be/~psmets/#G ''Software for TBM in Matlab'']

			[[Category:Logic]]
			[[Category:Statistical inference]]

en>Art Carlson: Undid revision 453665772 by 88.80.251.34 (talk) This is correct. If you have a question, ask on the talk page, not in the article.

2011-10-04T07:45:07Z

Undid revision 453665772 by 88.80.251.34 (talk) This is correct. If you have a question, ask on the talk page, not in the article.

New page

Hi there. My title is Garland even though it is not the name on my beginning certification. Interviewing is what she does but quickly she'll be on her own. One of my preferred hobbies is tenting and now I'm trying to earn cash with it. Delaware is our birth place.<br><br>my page ... [http://Freebusinesscollege.com//read_blog/198199/great-ideas-about-auto-repair-that-anyone-can-use freebusinesscollege.com]