Optimizing support vector machine parameters using cuckoo search algorithm via cross validation
© 2016 IEEE. Support vector machine is one of the most popular techniques for solving classification problems. It is known that the choice of parameters directly affects its performance. This problem can be solved using a search algorithm which is suitable optimization technique for the parameter op...
Saved in:
Main Authors: | Akkawat Puntura, Nipon Theera-Umpon, Sansanee Auephanwiriyakul |
---|---|
Format: | Conference Proceeding |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018951618&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57090 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
Optimizing support vector machine parameters using cuckoo search algorithm via cross validation
by: Akkawat Puntura, et al.
Published: (2018) -
Optimizing support vector machine parameters using cuckoo search algorithm via cross validation
by: Puntura A., et al.
Published: (2017) -
Fuzzy multilayer perceptron with cuckoo search
by: Suwannee Phitakwinai, et al.
Published: (2018) -
Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting
by: Suwannee Phitakwinai, et al.
Published: (2018) -
Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting
by: Phitakwinai S., et al.
Published: (2017)