DocumentCode :
260778
Title :
Nepotism responsive of data mining for prejudice inimitability
Author :
Saravanan, C. Bala ; Sugumar, R.
Author_Institution :
I.T Dept., VelTech Multitech Eng. Coll., Chennai, India
fYear :
2014
fDate :
27-28 Feb. 2014
Firstpage :
1
Lastpage :
3
Abstract :
In the milieu of civil rights law, favoritism refers to undue or crooked healing of people based on affiliate-ship to a sort or a marginal, without gaze at to dignitary merit. Rules extract from statistics bases by in filament mining piece, such as classification or pact rules, when used for verdict tasks such as benefit or acclaim endorsement, can be prejudiced in the above sense. In this paper, the impression of inequitable classification rules is forging and premeditated. On stipulation that a pledge of non-favoritism is exposed to be a non-trivial task. A naive loom, like captivating away all bigoted constituencies, is exposed to be not ample when other milieu fluency is available. Loom lead to a strict formulation of the redlining crisis alongside with a ritual corollary pertaining to prejudiced rules with apparently safe ones by affluence of milieu acuity.
Keywords :
data mining; pattern classification; civil rights law; classification rules; data mining; favoritism; filament mining piece; nepotism responsive; pact rules; prejudice inimitability; ritual corollary; rule extraction; verdict tasks; Association rules; Computer science; Educational institutions; Ethics; Facsimile; Tutorials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
Type :
conf
DOI :
10.1109/ICICES.2014.7033813
Filename :
7033813
Link To Document :
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