TRAINING SAMPLE DIMENSION REDUCTION BASED ON ASSOCIATION RULES
Науковий журнал «Радіоелектроніка, інформатика, управління»
Переглянути архів Інформація| Поле | Співвідношення | |
| ##plugins.schemas.marc.fields.042.name## |
dc |
|
| ##plugins.schemas.marc.fields.245.name## |
TRAINING SAMPLE DIMENSION REDUCTION BASED ON ASSOCIATION RULES |
|
| ##plugins.schemas.marc.fields.720.name## |
Zayko, T.; Zaporizhzhya National Technical University, Ukraine Oliinyk, A.; Zaporizhzhya National Technical University, Ukraine Subbotin, S.; Zaporizhzhya National Technical University, Ukraine |
|
| ##plugins.schemas.marc.fields.653.name## |
association rule, confidence, model, support, reduction, training sample, term. |
|
| ##plugins.schemas.marc.fields.520.name## |
The problem of training sample reduction is considered. A method for data reduction based on association rules is developed. The proposed method of training sample dimensionality reduction includes stages of reduction of instances, features and redundant terms, to evaluate the informativety of features uses the information about the extracted association rules. The developed method allows to create a partition of the feature space with less examples than in the original sample, which in turn allows the synthesis of simpler and more convenient for the perception of the diagnostic model. The practical value of these results is that on the basis of the proposed method the practical problem of reducing the training sample for the synthesis of the diagnostic model of quality confectionery products is solved. |
|
| ##plugins.schemas.marc.fields.260.name## |
Zaporizhzhya National Technical University 2014-08-20 00:00:00 |
|
| ##plugins.schemas.marc.fields.856.name## |
application/pdf http://ric.zntu.edu.ua/article/view/27280 |
|
| ##plugins.schemas.marc.fields.786.name## |
Radio Electronics, Computer Science, Control; No 1 (2014): Radio Electronics, Computer Science, Control |
|
| ##plugins.schemas.marc.fields.546.name## |
uk |
|
| ##plugins.schemas.marc.fields.540.name## |
Copyright (c) 2014 T. Zayko, A. Oliinyk, S. Subbotin |
|