Temporal and Frequential Metric Learning for Time Series kNN Classification

Abstract : In order to classify time series, many machine learning algorithms such as the kNN classifer require a metric. We propose in this work a framework to learn a combination of multiple metrics for a robust kNN classifier. This combined metric includes both temporal (value and behavior) and frequential components. By introducing the concept of pairwise space, the combination function is learned in this new space through a "large margin" optimization process. The efficiency of the learned metric is compared to the major alternative metrics on large public datasets.
Type de document :
Communication dans un congrès
ECML-PKDD, Sep 2015, Porto, Portugal
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01208429
Contributeur : Ahlame Douzal <>
Soumis le : vendredi 2 octobre 2015 - 15:34:39
Dernière modification le : samedi 12 décembre 2015 - 01:01:08

Identifiants

  • HAL Id : hal-01208429, version 1

Collections

Citation

Cao-Tri Do, Ahlame Douzal-Chouakria, Sylvain Marié, Michèle Rombaut. Temporal and Frequential Metric Learning for Time Series kNN Classification. ECML-PKDD, Sep 2015, Porto, Portugal. 〈hal-01208429〉

Partager

Métriques

Consultations de la notice

434