Algorithms Analysis in Adjusting the SVM Parameters: An Approach in the Prediction of Protein Function
Support Vector Machine (SVM) is a supervised learning algorithm widely used in data classification problems. However, the quality of the solution is related to the chosen kernel function, and the adjustment of its parameters. In the present study we compare a genetic algorithm (GA), a particle swarm...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-04-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2017.1317207 |