A Statistical Binary Classifier: Probabilistic Vector Machine

被引：0
|
作者：
Cimpoesu, Mihai [1 ]
Sucila, Andrei [1 ]
Luchian, Henri [1 ]
机构：
[1] Alexandru Ioan Cuza Univ, Fac Comp Sci, Iasi, Romania
来源：
PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2013 | 2013年 / 8154卷
关键词：
binary classification; hyperplane classifier; SVM; probabilistic; statistical model; kernel;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：211 / 222
页数：12
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