Reparation in Evolutionary Algorithms for Multi-objective Feature Selection in Large Software Product Lines
نویسندگان
چکیده
منابع مشابه
Evolutionary Multi-Objective Feature Selection
Feature selection is one of the most pervasive problems in pattern recognition. It can be posed as a multiobjective optimisation problem, since, in the simplest case, it involves feature subset cardinality minimisation and performance maximisation. In many problem domains, such as in medical or engineering diagnosis, performance can more appropriately be assessed by ROC analysis, in terms of cl...
متن کاملAn Evolutionary Methodology for Optimized Feature Selection in Software Product Lines
Feature modeling is the primary technology to capture and document the commonalities and variability among all of the members in a product line. Individual products are customized by selecting features according to the requirements. The work of feature selection is complex because of: 1) the complex dependencies and constraint relationship amongst features; 2) the multiple competing and conflic...
متن کاملMaximising Hypervolume for Selection in Multi-objective Evolutionary Algorithms [CEC7721]
When hypervolume is used as part of the selection or archiving process in a multi-objective evolutionary algorithm, the basic requirement is to choose a subset of the solutions in a non-dominated front such that the hypervolume of the subset is maximised. We describe and evaluate two algorithms to approximate this process: a greedy algorithm that assesses and eliminates solutions individually, ...
متن کاملMulti-objective Evolutionary Algorithms for filter Based Feature Selection in Classification
Feature selection is a multi-objective problem with the two main conflicting objectives of minimising the number of features and maximising the classification performance. However, most existing feature selection algorithms are single objective and do not appropriately reflect the actual need. There are a small number of multi-objective feature selection algorithms, which are wrapper based and ...
متن کاملMulti-Objective Evolutionary Algorithms for Feature Selection: Application in Bankruptcy Prediction
A Multi-Objective Evolutionary Algorithm (MOEA) was adapted in order to deal with problems of feature selection in datamining. The aim is to maximize the accuracy of the classifier and/or to minimize the errors produced while minimizing the number of features necessary. A Support Vector Machines (SVM) classifier was adopted. Simultaneously, the parameters required by the classifier were also op...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SN Computer Science
سال: 2021
ISSN: 2662-995X,2661-8907
DOI: 10.1007/s42979-021-00541-8