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Abstract: This report presents a new methodology of learning from examples, based on feature partitioning. Classification by Feature Partitioning (CFP) is a particular implementation of this technique, which is an inductive, incremental, and supervised learning method. Learning in CFP is accomplished by storing the objects separately in each feature dimension as disjoint partitions of values. A partition, a basic unit of representation which is initially a point in the feature dimension, is expanded... (Update)
Context of citations to this paper: More
...it is generalized to cover the new feature value. Otherwise, a new point partition that corresponds to the new feature value, is inserted [7]. A version of CFP called GACFP has been implemented to learn these parameters of the CFP using a genetic algorithm [4] No similarity and...
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BibTeX entry: (Update)
I. S¸irin, "Learning with Feature Partitions" M.Sc. Thesis, Bilkent University, Dept. of Computer Engineering and Info. Sci., Tech. Rep. No. BU-CEIS-9312. http://citeseer.ist.psu.edu/sirin94learning.html More
@misc{ irin-learning,
author = "I. irin",
title = "Learning with Feature Partitions",
text = "I. S¸irin, Learning with Feature Partitions M.Sc. Thesis, Bilkent University,
Dept. of Computer Engineering and Info. Sci., Tech. Rep. No. BU-CEIS-9312.",
url = "citeseer.ist.psu.edu/sirin94learning.html" }
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2 a Method for Classification Based on Feature Partitioning (context) - Guvenir, irin et al. - 1993
1 Prediction of Stock Market Index Changes - irin, Guvenir - 1993
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