Feature interval learning algorithms for classification
نویسندگان
چکیده
منابع مشابه
Feature interval learning algorithms for classification
This paper presents Feature Interval Learning algorithms (FIL) which represent multi-concept descriptions in the form of disjoint feature intervals. The FIL algorithms are batch supervised inductive learning algorithms and use feature projections of the training instances to represent induced classification knowledge. The concept description is learned separately for each feature and is in the ...
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ژورنال
عنوان ژورنال: Knowledge-Based Systems
سال: 2010
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2010.02.002