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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Berikov, V. |
| Copyright Year | 2003 |
| Description | Author affiliation: Novosibirsk State Tech. Univ., Russia (Berikov, V.) |
| Abstract | We consider a problem of pattern classifier performance evaluation in case of learning sample of limited size and discrete space of variables. The principle of Bayesian averaging of recognition performance is used for the analysis. With use of this principle, we found the dependencies between sample size, complexity of variables space, and the mean and variance of the true error function. This gives us a possibility to evaluate the confidence bound for the true error. As an application of these results, we consider the problem of classification tree design and evaluation of its performance. |
| Starting Page | 201 |
| Ending Page | 205 |
| File Size | 258710 |
| Page Count | 5 |
| File Format | |
| ISBN | 8978686176 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-06-28 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | 7th Korea-Russia Intl Sym on Science |
| Subject Keyword | Pattern recognition Bayesian methods Performance analysis Error analysis Probability distribution Mathematics Electronic mail Classification tree analysis Decision trees Analysis of variance |
| Content Type | Text |
| Resource Type | Article |
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