Application of Optimized SVM in Sample Classification

Application of Optimized SVM in Sample Classification

Support vector machines (SVM) have unique advantages in solving problems with small samples, nonlinearity and high dimension. It has a relatively complete theory and has been widely used in various fields. The classification accuracy and generalization ability of SVMs are determined by the selected...

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Bibliographic Details
Main Author: Yao, X. (Author)
Format: Article
Language:English
Published: Science and Information Organization 2022
Subjects:
Backpropagation
Classification accuracy
Complete theory
Cross-validation methods
Decision trees
Genetic algorithms
Higher dimensions
K fold cross validations
K-fold cross validation
Machine parameters
Mean square error
Neural networks
Parameter optimization
Particle swarm optimization (PSO)
Sample classification
Small samples
Support vector machine
Support vector machines
Support vectors machine
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