| Title |
A hybrid method for textual data classification based on support vector machine with particle swarm optimization metaheuristic and k-means clustering / |
| Authors |
Korovkinas, Konstantinas |
| Full Text |
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| Is Part of |
Joint Proceedings of Baltic DB&IS 2020 Conference Forum and Doctoral Consortium co-located with the 14th International Baltic Conference on Databases and Information Systems (BalticDB&IS 2020) Tallinn, Estonia, June 16-19, 2020.. CEUR-WS. 2020, p. 81-88 |
| Keywords [eng] |
K-Means ; particle swarm optimization ; support vector machine ; textual data classication |
| Abstract [eng] |
This paper introduces a hybrid method for textual data classication. The goal of this paper is to improve classication accuracy of method presented in our previous work by integrating to it k-Means method for decreasing training dataset and particle swarm optimization metaheuristic for a linear support vector machine parameter tuning. The paper reports that the introduced method is characterized by higher improvements in all effectiveness metrics than the methods presented in our previous works. |
| Published |
CEUR-WS |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2020 |
| CC license |
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