In this study, a hybrid and layered Intrusion Detection System (IDS) is proposed that uses a
combination of different machine learning and feature selection techniques to provide high …

Feature selection is a technique to choose a subset of variables from the multidimensional
data which can improve the classification accuracy in diversity datasets. In addition, the best …

Communication triggered for cell survival/apoptosis is achieved by three different input
proteins. In this paper, we have considered the heat map image that shows 11 different …

Educational data mining (EDM) evaluates and predicts students' performance that assists to
discover important factors affecting students' academic performance and also guides …

Objectives: This study summarizes the feature selection process, its importance, different
types of feature selection algorithms such as Filter, Wrapper and Hybrid. Moreover, it …

One of the most important classification problems is selecting proper features, ie features
that describe the classified object in the most straightforward way possible. Then, one of the …

Municipalities make significant efforts with limited resources to collect pavement condition
data. Overall Condition Index (OCI), which uses the pavement surface evaluation and rating …

The objective of this paper is to analyze the data of liver diseases using particle swarm
optimization algorithm (PSO) with KStar Classification, in two aspects for classifying the …

Medicine and especially chronic diseases, like everything else on earth is filled with
ambiguity. This is why, identifying patients at risk present a big challenge to human brain …

Background: In point of mortality rate, stomach cancer is the fifth leading cancer. There are
some risk factors of stomach cancer those are varied with country to country and associated …