The third is a novel heuristic feature selection algorithm with effectiveness but without overfitting problem. Experimental results convince our model acquires ...

Abstract: With a deeper investigation to deciphering the sophisticated relations among input and output variables of multi-class classification problems, ...

Our model devotes to three accomplishments of multi-class classification tasks. Feature discretization using fuzzy clustering analysis for the improvement of ...

Heuristic Feature Selection with Classification Efficiency. Using Soft Cluster Analysis for Biological Datasets. HUNG-Yl LIN - AND RONG-CHANG CHEN. Department ...

ABSTRACT. The goal of this paper is to propose a new feature selection model which enhances the discrimination power of the selected feature.

Abstract. This paper deals with supervised classification and feature selection with application in the context of high dimensional features.

Heuristic Feature Selection with Classification Efficiency Using Soft Cluster Analysis for Biological Datasets · Journal paper review · Knowledge-Based Systems.

Clustering is a long-standing problem in computer science and is applied in virtually any scientific field for exploring the inherent structure of datasets.

We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster ...