This paper presents a quality enhancement of the selected features by a hybrid filter-based
jointly on feature ranking and feature subset selection (FR-FSS) using a consistency-based …

This paper addresses the situation that may happen after the application of feature subset
selection in terms of a reduced number of selected features or even same solutions obtained …

This paper introduces an approach to feature subset selection which is able to characterise
the attributes of a supervised machine learning problem into two categories: essential and …

The nonlinear activation functions applied by each neuron in a neural network are essential
for making neural networks powerful representational models. If these are omitted, even …

This paper presents a novel procedure to apply in a sequential way two data preparation
techniques from a different nature such as data cleansing and feature selection. For the …

This paper proposes a methodology to feature sorting in the context of supervised machine
learning algorithms. Feature sorting is defined as a procedure to order the initial …

This paper develops three frameworks based on a metaheuristic algorithm to train neural
network classifiers. The architecture is a single‐hidden‐layer feedforward network. The first …

This paper proposes a methodology to feature sorting in the context of supervised machine
learning algorithms. Feature sorting is defined as a procedure to order the initial …

Product unit neural networks (PUNNs) are powerful representational models with a strong
theoretical basis, but have proven to be difficult to train with gradient-based optimizers. We …

NEURAL NETWORKS BASED ON RADIAL BASIS FUNCTION IN HIGH DIMENSION DOMAINS
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