A binary classification algorithm, called Probabilistic Vector Machine - PVM, is proposed. It is based on statistical measurements of the training data, providing a robust and lightweight classification model with reliable performance. The proposed model is also shown to provide the optimal binary classifier, in terms of probability of error, under a set of loose conditions regarding the data distribution. We compare PVM against GEPSVM and PSVM and provide evidence of superior performance on a number of datasets in terms of average accuracy and standard deviation of accuracy. © 2013 Springer-Verlag.
CITATION STYLE
Cimpoeşu, M., Sucilǎ, A., & Luchian, H. (2013). A statistical binary classifier: Probabilistic vector machine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8154 LNAI, pp. 211–222). https://doi.org/10.1007/978-3-642-40669-0_19
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