Converting numerical classification into text classification
نویسندگان
چکیده
منابع مشابه
Binning: Converting Numerical Classification into Text Classification
Consider a supervised learning problem in which examples contain both numericaland text-valued features. One common approach to this problem would be to treat the presence or absence of a word as a Boolean feature, which when combined with the other numerical features enables the application of a range of traditional feature-vector-based learning methods. This paper presents an alternative appr...
متن کاملConverting numerical classification into text classification
Consider a supervised learning problem in which examples contain both numericaland textvalued features. To use traditional feature-vector-based learning methods, one could treat the presence or absence of a word as a Boolean feature and use these binary-valued features together with the numerical features. However, the use of a text-classification system on this is a bit more problematic—in the...
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Consider a supervised learning problem in which examples contain both numericaland text-valued features. To use traditional featurevector-based learning methods, one could treat the presence or absence of a word as a Boolean feature and use these binary-valued features together with the numerical features. However, the use of a text-classification system on this is a bit more problematic — in t...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2003
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(02)00359-4