Neural networks and genetic algorithms are the two sophisticated machine learning
techniques presently attracting attention from scientists, engineers, and statisticians, among …

Fuzzy rough set method provides an effective approach to data mining and knowledge
discovery from hybrid data including categorical values and numerical values. However, its …

Neocortical structures typically only support slow acquisition of declarative memory;
however, learning through fast mapping may facilitate rapid learning‐induced cortical …

Abstract “Concept drift” and class imbalance are two challenges for supervised
classifiers.“Concept drift”(or non-stationarity) is changes in the underlying function being …

Abstract International Journal of Machine Learning and Cybernetics (IJMLC) is one of the
influential journals in the area of computer science, and it published its first issue in 2010 …

In real-world applications, the test cost of data collection should not exceed a given budget.
The problem of selecting an informative feature subset under this budget is referred to as …

Using two distinct data sets (from the USA and Germany) of healthy controls and patients
with early or mild stages of Parkinson's disease, we show that machine learning tools can be …

The security of programmable logic controllers (PLCs) that control industrial systems is
becoming increasingly critical due to the ubiquity of the Internet of Things technologies and …

In this paper we propose a novel method combining graph embedding and difference
criterion techniques for image feature extraction, namely two-dimensional maximum …

Feature selection is quite an important process in gene expression data analysis. Feature
selection methods discard unimportant genes from several thousands of genes for finding …