Book ChapterDOI
Hybrid ACO Chaos-Assisted Support Vector Machines for Classification of Medical Datasets
Gunjan Mishra,Vivek Ananth,Kalpesh Shelke,Deepak Sehgal,Jayaraman Valadi +4 more
- Vol. 336, pp 91-101
Reads0
Chats0
TLDR
This work employs a hybrid filter–wrapper approach to build high-performance classification models and indicates that the hybrid algorithm can discover informative subsets possessing very high classification accuracy.Abstract:
There is a need for developing accurate learning algorithms for analyzing large-scale medical diagnostic, prognostic, and treatment datasets. Success of classifiers like support vector machines lies in employment of best informative features out of a huge noisy feature space. In this work, we employ a hybrid filter–wrapper approach to build high-performance classification models. We tested our algorithms using popular datasets containing clinic-bio-pathological parameters of leukemia, hepatitis, breast cancer, and colon cancer taken from publically available datasets. Our results indicate that the hybrid algorithm can discover informative subsets possessing very high classification accuracy.read more
Citations
More filters
Journal ArticleDOI
Sine---cosine algorithm for feature selection with elitism strategy and new updating mechanism
TL;DR: Improved version of SCA with Elitism strategy and new best solution update mechanism is proposed to select best features/attributes to improve the classification accuracy and it can be seen that pattern classification using ISCA has been commendable in achieving better classification performance.
Journal Article
Ant Colony Optimization
TL;DR: This work has shown that artificial ants in ACO essentially are randomized construction procedures that generate solutions based on (artificial) pheromone trails and heuristic information that are associated to solution components.
References
More filters
Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TL;DR: Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Journal ArticleDOI
The WEKA data mining software: an update
TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Journal ArticleDOI
An introduction to variable and feature selection
Isabelle Guyon,André Elisseeff +1 more
TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.