Abstract This article performs a detailed data scrutiny on chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, handling of missing values. that do not influence the target are removed envelopment analysis enable reduction rows. Column achieved by ranking attributes through se...

in the  present study, after investigating the theoretical bases and results of previous  researches and identifying the most important indicators and sub-indicators of human resource management affecting organizational performance, weighting and ranking the indicators were performed using the questionnaire (first) and applying the fuzzy ahp technique, in which the highest ranks were allocated ...

A target-based MADM method covers beneficial and non-beneficial attributes besides target values for some attributes. Such techniques are considered as the comprehensive forms of MADM approaches. Target-based MADM methods can also be used in traditional decision-making problems in which beneficial and non-beneficial attributes only exist. In many practical selection problems, some attributes ha...

This paper outlines a feasible approach to ranking Grid resources based on an easily obtainable application-specific performance model utilizing low-level performance metrics. First, Grid resources are characterized using lowlevel performance metrics; Then the performance of a given application is associated to the low-level performance measurements via a Ranking Function; Finally, the Ranking ...

 In this paper, we propose a new gene selection algorithm based on Shuffled Frog Leaping Algorithm that is called SFLA-FS. The proposed algorithm is used for improving cancer classification accuracy. Most of the biological datasets such as cancer datasets have a large number of genes and few samples. However, most of these genes are not usable in some tasks for example in cancer classification....

Feature selection is a data processing method which aims to select effective feature subsets from original features. based on evolutionary computation (EC) algorithms can often achieve better classification performance because of their global search ability. However, methods using EC cannot get rid invalid features effectively. A small number still exist till the termination algorithms. In this...