Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines
A good selection of Least Squares Support Vector Machines (LSSVM) hyper-parameters' value is crucial in order to obtain a promising generalization on the unseen data. Any inappropriate value set to the hyper parameters would directly demote the prediction performance of LSSVM. In this regard,...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publishing Network (ARPN)
2015
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/16363/1/PRICE%20PREDICTIVE%20ANALYSIS%20MECHANISM%20UTILIZING%20GREY%20WOLF_ARPN.pdf http://umpir.ump.edu.my/id/eprint/16363/ http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1215_3198.pdf |
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