Classification is a data mining technique which is utilized to predict the future by using
available data and aims to discover hidden relationships between variables and classes …

For a variety of applications, machine learning algorithms are required to construct models
that minimize the total loss associated with the decisions, rather than the number of errors …

This paper addresses two cost-sensitive learning methodology issues. First, we ask the
question of whether Bagging is always an appropriate procedure to compute accurate class …

This paper presents deep learning models for binary and multiclass intrusion classification
problems in Software-defined-networks (SDN). The induced models are evaluated by the …

As an early stage of Alzheimer's disease (AD), the accurate detection of mild cognitive
impairment (MCI) is very important for its early intervention. Due to the small between-group …

In recent years, the increase in the demand for credit leads the financial institutions to
consider artificial intelligence and machine learning techniques as a solution to make …

Abstract Recently, Freund, Mansour and Schapire established that using exponential
weighting scheme in combining classifiers reduces the problem of overfitting. Also …

In the past few years, a growing demand for credit compel banking institution to contemplate
machine learning techniques as an answer to obtain decisions in a reduced time. Different …

In this paper, we are proposing an efficient method of classifying form that is applicable in
real life. Our method will identify a small number of local regions by their distinctive images …

In several predictive tasks the end-user attention is focused in certain regions of the domain
of the target variable. As opposed to standard predictive tasks where all target variable …