| Title |
Daugelio klasių atpažinimas naudojant klasifikatorius poroms / |
| Translation of Title |
Multi-class recognition using pair-wise classifiers. |
| Authors |
Kybartas, Rimantas |
| Full Text |
|
| Pages |
36 |
| Keywords [eng] |
multi-class classification ; single layer perceptron ; pair-wise classification |
| Abstract [eng] |
There are plenty of solutions for the task of multi-class recognition. Unfortunately, these solutions are not always unanimous. Most of them are based on empirical experiments while statistical data features consideration is often omitted. That’s why questions like when and which method should be used, what the reliability of any chosen method is for solving a multi-class recognition task arise. In this dissertation two-stage multi-class decision methods are analyzed. Pair-wise classifiers able to better exploit statistical data features are used in the first stage of such methods. In the second stage a particular fusion rule of the first stage results is used to fuse the first stage results in order to produce the final classification decision. Complexity issues of pair-wise classifiers, training data size and precision of method quality estimation are pointed out in the research. The precision of algorithm highly depends on the data and the number of experiments performed (data permutation, division into training and testing data). It is shown that the declared superiority of some known algorithms is not reliable due to low precision of estimation. A detailed comparison of well known multi-class classification methods is performed and a new pair-wise classifier fusion method based on similar method used in multi-class classifier fusion is presented. The recommendations for multi-class classification task designer are provided. Methods which allow reducing classification error by classification method correction in order to get less bias to training data are proposed. The results of research are applied to a complex geological data classification task. |
| Type |
Summaries of doctoral thesis |
| Language |
Lithuanian |
| Publication date |
2010 |
