Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …

In April 1981 Xerox announced the 8010 Star Information System, a new personal computer
designed for office professionals who create, analyze, and distribute information. The Star …

Feature selection is of considerable importance in data mining and machine learning,
especially for high dimensional data. In this paper, we propose a novel nearest neighbor …

Variable and feature selection have become the focus of much research in areas of
application for which datasets with tens or hundreds of thousands of variables are available …

Support vector machines (SVM) are attractive for the classification of remotely sensed data
with some claims that the method is insensitive to the dimensionality of the data and …

Feature selection aims at finding the most relevant features of a problem domain. It is very
helpful in improving computational speed and prediction accuracy. However, identification of …

Adequate selection of features may improve accuracy and efficiency of classifier methods.
There are two main approaches for feature selection: wrapper methods, in which the …

Abstract Machine learning methods are promising to predict key properties of concrete and
expedite design of advanced concrete, but the existing methods have limitations in accuracy …

This paper explores the relationship between the features of Bitcoin and the next day
change in the price of Bitcoin using an Artificial Neural Network ensemble approach called …

One of the fundamental motivations for feature selection is to overcome the curse of
dimensionality problem. This paper presents a novel feature selection method utilizing a …