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Álvar Arnaiz-González

3 papers hereh-index 18960 citations57 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedFeature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale

14 citations · 14 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2025

Remote sensing colour image semantic segmentation of trails created by large herbivorous Mammals

Jose Francisco Diez-Pastor, Francisco Javier Gonzalez-Moya, Pedro Latorre-Carmona +5

Identifying spatial regions where biodiversity is threatened is crucial for effective ecosystem conservation and monitoring. In this stydy, we assessed varios machine learning meth…

cs.LG2020★ 14 cited

Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale

Ludmila I. Kuncheva, Clare E. Matthews, Álvar Arnaiz-González +1

In classification problems, the purpose of feature selection is to identify a small, highly discriminative subset of the original feature set. In many applications, the dataset may…

cs.CV2018

Instance Selection Improves Geometric Mean Accuracy: A Study on Imbalanced Data Classification

Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor +1

A natural way of handling imbalanced data is to attempt to equalise the class frequencies and train the classifier of choice on balanced data. For two-class imbalanced problems, th…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.