Learning from Little: Comparison of Classifiers Given Little Training (2004)
by
George Forman
,
Ira Cohen
| Venue: | in 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD |
| Citations: | 14 - 4 self |
BibTeX
@INPROCEEDINGS{Forman04learningfrom,
author = {George Forman and Ira Cohen},
title = {Learning from Little: Comparison of Classifiers Given Little Training},
booktitle = {in 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD},
year = {2004},
pages = {161--172}
}
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Abstract
Many real-world machine learning tasks are faced with the problem of small training sets. Additionally, the class distribution of the training set often does not match the target distribution. In this paper we compare the performance of many learning models on a substantial benchmark of binary text classification tasks having small training sets.
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