DocumentCode :
1772603
Title :
Monte Carlo simulation based algorithm design for automatic learning machine performance analysis
Author :
Tigani, Smail ; Ouzzif, Mouhamed ; Hasbi, Abderrahim
Author_Institution :
Comput. Sci. Dept., Nat. High Sch. of Electr. & Mech., Casablanca, Morocco
fYear :
2014
fDate :
28-30 May 2014
Firstpage :
19
Lastpage :
21
Abstract :
This paper proposes advanced key performance indicators dedicated to learning machines and auto-adaptive systems performance analysis. This work introduces an algorithm implementing designed key performance indicators for automatic learning capacity checking. The algorithm simulates the supervised environment to stimulate the tested auto-adaptive machine and then study its adaption capacity based on indicators statistically designed.
Keywords :
Monte Carlo methods; learning (artificial intelligence); Monte Carlo simulation based algorithm design; advanced key performance indicators; autoadaptive machine; autoadaptive system performance analysis; automatic learning capacity checking; automatic learning machine performance analysis; Algorithm design and analysis; Linear regression; Mathematical model; Monte Carlo methods; Prediction algorithms; Predictive models; Vectors; Automatic Learning; Key Performance Indicator; Linear Regression; Monte Carlo Simulation; Prediction Algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Next Generation Networks and Services (NGNS), 2014 Fifth International Conference on
Conference_Location :
Casablanca
Print_ISBN :
978-1-4799-6608-0
Type :
conf
DOI :
10.1109/NGNS.2014.6990221
Filename :
6990221
Link To Document :
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