Evolutionary Multi-Objective Feature Selection
نویسنده
چکیده
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 classifier specificity and sensitivity. This paper presents a natural way of handling such objectives in feature selection by multi-objective evolutionary algorithms. Results demonstrating the applicability of the approach in feature selection for industrial machinery fault diagnosis and on a benchmarking data set are provided.
منابع مشابه
Feature Selection Using Multi Objective Genetic Algorithm with Support Vector Machine
Different approaches have been proposed for feature selection to obtain suitable features subset among all features. These methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. The objective functions are divided into two main groups: filter and wrapper methods. In filter methods, features subsets are selected due to some measu...
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 کاملMeasuring the Performance of Evolutionary Multi-Objective Feature Selection for Prediction of Musical Genres and Styles
The prediction of high-level music categories, such as genres, styles, or personal preferences, helps to organise music collections. The relevance of single audio features for automatic classification depends on a certain category. Relevant feature subsets for each classification task can be identified by means of feature selection. Continuing our previous studies on multi-objective feature sel...
متن کاملMulti-Objective Feature Subset Selection using Non-dominated Sorting Genetic Algorithm
This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, t...
متن کاملImproving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...
متن کامل