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首页> 外文期刊>International Journal of Innovative Computing Information and Control >A NEW MUTATION OPERATION FOR FASTER CONVERGENCE IN GENETIC ALGORITHM FEATURE SELECTION
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A NEW MUTATION OPERATION FOR FASTER CONVERGENCE IN GENETIC ALGORITHM FEATURE SELECTION

机译：遗传算法特征选择中更快收敛的新突变运算

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摘要

Feature selection is an important step in data classification because it has a high impact on classification accuracy. Feature selection using Genetic Algorithm (GA) is usually done in a wrapper method. The process is time consuming especially for large dimensional database. We propose a new mutation operation for faster feature selection by GA based on elitism of the allele. Normal elitism in GA preserves the most fit chromosomes which are evaluated using the fitness function. In the same way, the highest fit allele will be preserved and the fitness of the allele is evaluated based on the frequency of occurrences. The chromosome undergoing this mutation process will have a high if not the highest fitness because it is created based on a high fit allele. It will be the catalyst to increase the rate of convergence towards achieving an optimal features combination. Experiments for feature selection using this method are conducted using a database of tropical wood species which has a large variation of features. Results of the experiments show that a high accuracy is obtained for the recognition of the tropical wood species using the feature selection method. In addition, it has also been shown that the chromosomes created by the new mutation operation have high fitness and the rate of optimal convergence is improved substantially. The new mutation operation is not only useful for large database, but also can be used for small or medium sized database.
机译：特征选择是数据分类中的重要步骤，因为它对分类精度有很大影响。使用遗传算法（GA）进行特征选择通常是通过包装方法完成的。该过程非常耗时，特别是对于大型数据库。我们提出了一种新的突变操作，可以根据等位基因的优势通过GA更快地选择特征。遗传算法中的正常精英会保留最适合的染色体，并使用适应度函数对其进行评估。同样，将保留最适合的等位基因，并根据出现的频率评估等位基因的适应性。经历此突变过程的染色体，即使不是最高适应性也很高，因为它是基于高度适合的等位基因创建的。它将是提高收敛速度以实现最佳特征组合的催化剂。使用这种方法的特征选择实验是使用具有较大特征差异的热带木材物种数据库进行的。实验结果表明，使用特征选择方法能够获得较高的识别热带木材种类的准确性。另外，还表明通过新的突变操作产生的染色体具有很高的适应性，并且最佳收敛速度大大提高了。新的变异操作不仅适用于大型数据库，还可以用于中小型数据库。

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