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Comparison of Binary Classification Based on Signed Distance Functions with Support Vector Machines
2009
We compare methods based on the Signed Distance Function (SDF) a new tool for binary classification with standard Support Vector Machine (SVM) methods. We demonstrate on several sets of micro-array data that the performance of the SDF based methods can match or exceed that of SVM methods.
Keywords:
- Machine learning
- Kernel (linear algebra)
- Metric (mathematics)
- Structured support vector machine
- Signed distance function
- Support vector machine
- Binary classification
- Statistical classification
- k-nearest neighbors algorithm
- Computer science
- Artificial intelligence
- Pattern recognition
- Robustness (computer science)
- distance measurement
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