Myopic Policies in Sequential Classification
IEEE Transactions on Computers
Generalized error bounds in pattern recognition
Pattern Recognition Letters
Some properties of Rényi entropy over countably infinite alphabets
Problems of Information Transmission
| Hi-index | 754.84 |
The basic properties of Renyi's entropy are reviewed, and its concavity properties are characterized. New bounds (referred to asI_{alpha}bounds) on the probability of error are derived from Renyi's entropy and are compared with known bounds. It is proved that for the two-class case, theI_{2}bound is sharper than many of the previously known bounds. The difference between theI_{2}bound and the real value of the probability of error is at most 0.09.