Artificial intelligence (AI) research and market have grown rapidly in the last few years, and
this trend is expected to continue with many potential advancements and innovations in this …

Ensemble learning have emerged as a useful machine learning technique, which is based
on the idea that combining the output of multiple models instead of using a single model …

Artificial intelligence (AI) research and market have grown rapidly in the last few years and
this trend is expected to continue with many potential advancements and innovations in this …

Feature selection is a subfield of machine learning focused on reducing the dimensionality
of datasets by performing a computationally intensive process. This work presents Parallel …

Feature selection algorithms are necessary nowadays for machine learning as they are
capable of removing irrelevant and redundant information to reduce the dimensionality of …

In the presented study, the problem of interactive feature extraction, ie, supported by
interaction with users, is discussed, and several innovative approaches to automating …

Feature selection is the data analysis process that selects a smaller and curated subset of
the original dataset by filtering out data (features) which are irrelevant or redundant. The …

Computational methods are nowadays ubiquitous in the field of bioinformatics and
biomedicine. Besides established fields like molecular dynamics, genomics or …

In the dissertation, the problem of interactive feature extraction, ie, supported by interaction
with users, is discussed, and several innovative approaches to automating feature creation …

Na actualidade estase a producir un auxe da produción e consumo de grandes cantidades
de información (big data), que deben procesarse e prepararse para o seu posterior uso …