Abstract: Classification with empirically observed statistics is studied for finite alphabet sources. Efficient universal discriminant functions are ...
ISSN Information: Print ISSN: 0018-9448 Electronic ISSN: 1557-9654
DOI: 10.1109/18.2636
DOI: 10.1109/18.2636
Data Compression. Abstract -Classification with empirically observed statistics is studied for finite alphabet sources. Efficient universal discriminant ...
Bibliographic details on On classification with empirically observed statistics and universal data compression.
Classification with empirically observed statistics is studied for finite alphabet sources. Efficient universal discriminant functions are described and ...
We propose a classifier and analyze the type-I and type-II error probabilities. We demonstrate the significant advantage of our sequential scheme compared to an ...
Nov 30, 2022 · Motivated by real-world machine learning applications, we consider a statistical classification task in a sequential setting where test ...
binary classification problem and universal data compression methods. Unnikrishnan and Naini [5] and Unnikrishnan [6] extended Gutman's proposed test for ...
Dec 3, 2019 · Abstract: Motivated by real-world machine learning applications, we consider a statistical classification task in a sequential setting where ...
Missing: universal compression.
Feb 10, 2021 · relationship between test rules for the binary classification problem and universal data compression methods. Unnikrishnan and Naini [5].
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