Interactive Machine Learning - Letting Users Build Classifiers (2000)
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BibTeX
@MISC{Ware00interactivemachine,
author = {Malcolm Ware and Eibe Frank and Geoffrey Holmes and Mark Hall and Ian H. Witten},
title = {Interactive Machine Learning - Letting Users Build Classifiers},
year = {2000}
}
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Abstract
According to standard procedure, building a classier is a fully automated process that follows data preparation by a domain expert. In contrast, interactive machine learning engages users in actually generating the classier themselves. This oers a natural way of integrating background knowledge into the modeling stage|so long as interactive tools can be designed that support e- cient and eective communication. This paper shows that appropriate techniques can empower users to create models that compete with classiers built by state-of-the-art learning algorithms. It demonstrates that users| even users who are not domain experts| can often construct good classiers, without any help from a learning algorithm, using a simple two-dimensional visual interface. Experiments demonstrate that, not surprisingly, success hinges on the domain: if a few attributes can support good predictions, users generate accurate classiers, whereas domains with many high-order attrib...
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