Search
Now showing items 21-30 of 30
Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis
(Frontiers Media, 2022-06)
Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain ...
Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction
(Public Library Science, 2014-10-03)
Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different ...
Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems
(Elsevier, 2023-11)
Supervised and unsupervised classification is crucial in many areas where different types of data sets are common, such as biology, medicine, or industry, among others. A key consideration is that some units are more typical ...
Dynamic selection of the best base classifier in one versus one
(Elsevier, 2015-05-19)
Class binarization strategies decompose the original multi-class problem into several binary sub-problems. One versus One (OVO) is one of the most popular class binarization techniques, which considers every pair of classes ...
NewOneVersusOneAll method: NOV@
(Elsevier, 2014-04-19)
Binarization strategies decompose the original multi-class dataset into multiple two-class subsets, learning a different binary model for each new
subset. One-vs-All (OVA) and One-vs-One (OVO) are two of the most well-known ...
Undirected cyclic graph based multiclass pair-wise classifier: Classifier number reduction maintaining accuracy
(Elsevier, 2015-08-13)
Supervised Classification approaches try to classify correctly the new unlabelled examples based on a set of well-labelled samples. Nevertheless, some classification methods were formulated for binary classification problems ...
K nearest neighbor equality: giving equal chance to all existing classes
(Elsevier, 2011-07-23)
The nearest neighbor classification method assigns an unclassified point to the class of the nearest case of a set of previously classified points. This rule is independent of the underlying joint distribution of the sample ...
Classifier Subset Selection to construct multi-classifiers by means of estimation of distribution algorithms
(Elsevier, 2015-01-24)
This paper proposes a novel approach to select the individual classifiers to take part in a Multiple-Classifier System. Individual classifier selection is a key step in the development of multi-classifiers. Several works ...
dbcsp: User-friendly R package for Distance-Based Common Spatial Patterns
(The R Foundation, 2022-12-20)
Common Spatial Patterns (CSP) is a widely used method to analyse electroencephalography
(EEG) data, concerning the supervised classification of the activity of brain. More generally, it can
be useful to distinguish between ...
Online Student Authentication and Proctoring System Based on Multimodal Biometrics Technology
(2021-05-11)
Identity veri cation and proctoring of online students are one of the key challenges to online
learning today. Especially for online certi cation and accreditation, the training organizations need to verify
that the ...