Learning rule for linear multilayer feedforward ann by boosted decision stumps

Mirza Mubasher Baig; El Sayed M. El-Alfy; Mian M. Awais

doi:10.1007/978-3-319-26532-2_38

Learning rule for linear multilayer feedforward ann by boosted decision stumps

Mirza Mubasher Baig^*, El Sayed M. El-Alfy, Mian M. Awais

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

A novel method for learning a linear multilayer feedforward artificial neural network (ANN) by using ensembles of boosted decision stumps is presented. Network parameters are adapted through a layerwise iterative traversal of neurons with weights of each neuron learned by using a boosting based ensemble and an appropriate reduction. Performances of several neural network models using the proposed method are compared for a variety of datasets with networks learned using three other algorithms, namely Perceptron learning rule, gradient decent back propagation algorithm, and Boostron learning.

Original language	English
Title of host publication	Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
Editors	Weng Kin Lai, Qingshan Liu, Tingwen Huang, Sabri Arik
Publisher	Springer Verlag
Pages	345-353
Number of pages	9
ISBN (Print)	9783319265315
DOIs	https://doi.org/10.1007/978-3-319-26532-2_38
State	Published - 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9489
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-26532-2_38

Cite this

Baig, M. M., El-Alfy, E. S. M., & Awais, M. M. (2015). Learning rule for linear multilayer feedforward ann by boosted decision stumps. In W. K. Lai, Q. Liu, T. Huang, & S. Arik (Eds.), Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings (pp. 345-353). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9489). Springer Verlag. https://doi.org/10.1007/978-3-319-26532-2_38

Baig, Mirza Mubasher ; El-Alfy, El Sayed M. ; Awais, Mian M. / Learning rule for linear multilayer feedforward ann by boosted decision stumps. Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. editor / Weng Kin Lai ; Qingshan Liu ; Tingwen Huang ; Sabri Arik. Springer Verlag, 2015. pp. 345-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{3b2940bb819d4874bcbe435d088c4531,

title = "Learning rule for linear multilayer feedforward ann by boosted decision stumps",

abstract = "A novel method for learning a linear multilayer feedforward artificial neural network (ANN) by using ensembles of boosted decision stumps is presented. Network parameters are adapted through a layerwise iterative traversal of neurons with weights of each neuron learned by using a boosting based ensemble and an appropriate reduction. Performances of several neural network models using the proposed method are compared for a variety of datasets with networks learned using three other algorithms, namely Perceptron learning rule, gradient decent back propagation algorithm, and Boostron learning.",

author = "Baig, {Mirza Mubasher} and El-Alfy, {El Sayed M.} and Awais, {Mian M.}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.",

year = "2015",

doi = "10.1007/978-3-319-26532-2_38",

language = "English",

isbn = "9783319265315",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Baig, MM, El-Alfy, ESM & Awais, MM 2015, Learning rule for linear multilayer feedforward ann by boosted decision stumps. in WK Lai, Q Liu, T Huang & S Arik (eds), Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9489, Springer Verlag, pp. 345-353. https://doi.org/10.1007/978-3-319-26532-2_38

Learning rule for linear multilayer feedforward ann by boosted decision stumps. / Baig, Mirza Mubasher; El-Alfy, El Sayed M.; Awais, Mian M.
Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. ed. / Weng Kin Lai; Qingshan Liu; Tingwen Huang; Sabri Arik. Springer Verlag, 2015. p. 345-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9489).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Baig, Mirza Mubasher

AU - El-Alfy, El Sayed M.

AU - Awais, Mian M.

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AB - A novel method for learning a linear multilayer feedforward artificial neural network (ANN) by using ensembles of boosted decision stumps is presented. Network parameters are adapted through a layerwise iterative traversal of neurons with weights of each neuron learned by using a boosting based ensemble and an appropriate reduction. Performances of several neural network models using the proposed method are compared for a variety of datasets with networks learned using three other algorithms, namely Perceptron learning rule, gradient decent back propagation algorithm, and Boostron learning.

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BT - Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings

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Baig MM, El-Alfy ESM, Awais MM. Learning rule for linear multilayer feedforward ann by boosted decision stumps. In Lai WK, Liu Q, Huang T, Arik S, editors, Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. Springer Verlag. 2015. p. 345-353. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-26532-2_38

Learning rule for linear multilayer feedforward ann by boosted decision stumps

Abstract

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