Presentation | 1997/12/2 Efficient Construction of Regression Trees with Range and Region Splitting Hiromu Ishii, Yasuhiko Morimoto, Shinichi Morishita, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In recent years data mining has attracted many researchers among both artificial intelligence and database communities. Construction of regression trees is a topic of data mining. A regression tree is a rooted binary tree such that each internal node contains a test for splitting tuples into two disjoint classes. The mean of the objective attribute values at the leaf is used as the predicted value of the tuple. To test a numerical attribute, traditional methods use a guillotine-cut splitting that classifies data into those below a given value and others. In this paper, as an alternative of guillotine-cut splitting, we consider a family R of grid-regions in the plane associated with two given numeric attributes. And we propose to use a test that splits data into those that lie inside a region R and those that lie outside. Some experimental results showed that regression trees constructed through our method have higher accuracy than those through guillotine-cut splitting. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | data mining / numerical value prediction / regression tree / range and region splitting / convex function |
Paper # | DE97-76 |
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Committee | DE |
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Conference Date | 1997/12/2(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Data Engineering (DE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Efficient Construction of Regression Trees with Range and Region Splitting |
Sub Title (in English) | |
Keyword(1) | data mining |
Keyword(2) | numerical value prediction |
Keyword(3) | regression tree |
Keyword(4) | range and region splitting |
Keyword(5) | convex function |
1st Author's Name | Hiromu Ishii |
1st Author's Affiliation | Department of Information Science, University of Tokyo() |
2nd Author's Name | Yasuhiko Morimoto |
2nd Author's Affiliation | Tokyo Research Laboratory, IBM Japan Ltd. |
3rd Author's Name | Shinichi Morishita |
3rd Author's Affiliation | Institute of Medical Science, University of Tokyo |
Date | 1997/12/2 |
Paper # | DE97-76 |
Volume (vol) | vol.97 |
Number (no) | 417 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |