Parameter determination of support vector machine and feature selection using simulated annealing approach

By Shih-Wei Lin, Zne-Jung Lee, Shih-Chieh Chen, Tsung-Yuan Tseng. Applied Soft Computing, 2008

374 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/72a25ee8411f3d89ca6e51d66e5f8e01f71efbbd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yudong Zhang
2. Sarabjeet Singh Bedi
3. Genlin Ji
4. Shuihua Wang
5. Mayank Arya Chandra
6. Arash Bahrammirzaee

In Computer Vision and Pattern Recognition

1. Yudong Zhang
2. Sarabjeet Singh Bedi
3. Mayank Arya Chandra

Citations in the corpus

• Survey on SVM and their application in image classification (2018, methodology): “To resolve such type of cases, the SVM algorithm has introduced the new term known as ‘soft margin’ [14].”
• Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm (2016, neutral): “45 n/a n/a n/a n/a SVM + SA and FS [46] 99.”
• Binary PSO with mutation operator for feature selection using decision tree applied to spam detection (2014, methodology): “However, when using genetic algorithm (GA) or simulated annealing (SA) algorithm for FS, the results are sensitive to initial values and the computation times are too long [26, 27].”