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,...
| Main Authors: | Zuriani, Mustaffa, M. H., Sulaiman | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | 
        
      Asian Research Publishing Network (ARPN)    
    
      2015
     | 
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/16363/ http://umpir.ump.edu.my/id/eprint/16363/ http://umpir.ump.edu.my/id/eprint/16363/1/PRICE%20PREDICTIVE%20ANALYSIS%20MECHANISM%20UTILIZING%20GREY%20WOLF_ARPN.pdf  | 
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