Optimal Feature Selection from VMware ESXi 5.1 Feature Set

Optimal Feature Selection from VMware ESXi 5.1 Feature Set

A study of VMware ESXi 5.1 server has been carried out to find the optimal set of parameters which suggest usage of different resources of the server. Feature selection algorithms have been used to extract the optimum set of parameters of the data obtained from VMware ESXi 5.1 server using esxtop command. Multiple virtual machines (VMs) are running in the mentioned server. K-means algorithm is ...

Toward Optimal Feature Selection

In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for de ning the theoretically optimal, but computationally intractable, method for feature subset selection is presented. We show that our goal should be to eliminate a feature if it gives us little or no additional information beyond that subsumed by the remaining features. In pa...

The Architecture of VMware ESXi

Feature Selection: Near Set Approach

The problem considered in this paper is the description of objects that are, in some sense, qualitatively near each other and the selection of features useful in classifying near objects. The term qualitatively near is used here to mean closeness of descriptions or distinctive characteristics of objects. The solution to this twofold problem is inspired by the work of Zdzis law Pawlak during the...

Feature Usability Index and Optimal Feature Subset Selection

Feature usability index is introduced here as a measure for evaluating classification efficacy of features. It is defined using measures of homogeneity, class specificity, and error in decision making. Homogeneity measures the extent of outlying observations, class specificity assesses the separation between distributions of different labeled classes, and error in decision making is computed us...