Feature Selection using Simulated Annealing with Optimal Neighborhood Approach
نویسندگان
چکیده
Abstract The one of the metaheuristic approaches that can be used was simulated annealing (SA) algorithm which inspired by metallurgical process. This shows advantages in finding global optimum given function will feature selection. In this study, we trying to combine neighborhood size and limited approach using data simulation comparing between two is Akaike Index Criterion (AIC) Bayesian (BIC) function. result experiment selected variables optimal limit variable provide goodness model around 98% accuracy specificity 94% sensitivity compared with algorithms without any modification both AIC BIC function, also give better than
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ژورنال
عنوان ژورنال: Journal of physics
سال: 2021
ISSN: ['0022-3700', '1747-3721', '0368-3508', '1747-3713']
DOI: https://doi.org/10.1088/1742-6596/1752/1/012030