Visualización de conjuntos de datos de múltiples instancias

Jorge Eliecer Valencia-Duque, Carlos Mera, Lina Maria Sepúlveda

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

Resumen

In pattern recognition, multiple-instance learning algorithms have gained importance since they avoid that the user must delimit, the images individually in order to recognize the objects. This is an advantage over traditional learning algorithms since these considerably reduce the time required to prepare the data set. However, a disadvantage is that the resulting data sets are often complex, making it difficult to visualize them using traditional information visualization techniques. Thus, this work proposes a tool for the visualization and analysis of data sets of the multi-instance learning paradigm. The visualization proposal was evaluated using the expert criteria. In addition, different tests were carried out that show that a correct visualization can help to make decisions about the data set to improve the classification precision.

Título traducido de la contribuciónVisualization multi-instance data sets
Idioma originalEspañol
Páginas (desde-hasta)84-99
Número de páginas16
PublicaciónRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volumen2020
N.º39
DOI
EstadoPublicada - oct 2020

Palabras clave

  • Information visualization
  • Multi-instance learning
  • Representation
  • Visual Analysis

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