Result: Comparison of extreme learning machine with support vector machine for text classification

Title:
Comparison of extreme learning machine with support vector machine for text classification
Authors:
YING LIU, HAN TONG LOH, SHU BENG TOR
Source:
Innovations in applied artificial intelligence (Bari, 22-24 June 2005)Lecture notes in computer science. :390-399
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 26 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Algorithme apprentissage, Learning algorithm, Algoritmo aprendizaje, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Analyse contenu, Content analysis, Análisis contenido, Analyse régression, Regression analysis, Análisis regresión, Analyse statistique, Statistical analysis, Análisis estadístico, Classification, Clasificación, Evaluation performance, Performance evaluation, Evaluación prestación, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Intelligence économique, Competitive intelligence, Inteligencia economica, Machine exemple support, Vector support machine, Máquina ejemplo soporte, Recherche information, Information retrieval, Búsqueda información, Réseau neuronal, Neural network, Red neuronal
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Singapore-MIT Alliance, National University of Singapore, Singapore 117576, Singapore
Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798, Singapore
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=16991257
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16991257
Database:
PASCAL Archive

Further Information

Extreme Learning Machine, ELM, is a recently available learning algorithm for single layer feedforward neural network. Compared with classical learning algorithms in neural network, e.g. Back Propagation, ELM can achieve better performance with much shorter learning time. In the existing literature, its better performance and comparison with Support Vector Machine, SVM, over regression and general classification problems catch the attention of many researchers. In this paper, the comparison between ELM and SVM over a particular area of classification, i.e. text classification, is conducted. The results of benchmarking experiments with SVM show that for many categories SVM still outperforms ELM. It also suggests that other than accuracy, the indicator combining precision and recall, i.e. F1 value, is a better performance indicator.