Fuzzy Processing of Classification Samples Based on SVM Method
- Login to Download
- 1 Credits
Resource Overview
This program implements fuzzy processing of classification samples based on the Support Vector Machine (SVM) method, incorporating fuzzy factors to enhance classification precision through feature value adjustments.
Detailed Documentation
This program implements fuzzy processing of classification samples based on the Support Vector Machine (SVM) method to improve classification accuracy. During the fuzzy processing, fuzzy factors are introduced to fine-tune the feature values of samples, resulting in more precise and reliable classification outcomes. The implementation involves modifying standard SVM algorithms by applying fuzzy membership functions to input features, which helps handle uncertainties in data distribution and reduces misclassification rates near decision boundaries.
- Login to Download
- 1 Credits