Presentation 2018-11-05
[Poster Presentation] A Fast Approximation of the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel
Toshio Ito, Naoki Hamada, Kotaro Ohori, Hiroyuki Higuchi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) For a system with inputs and outputs, a nonparametric regression has been proposed to clarify the relationship between inputs and outputs from a large amount of data. To improve estimation accuracy for the Nadaraya-Watson regression which is one of the nonparametric regressions, the regression with $k$-nearest neighbor crossover kernel, in which the kernel function by using neighborhood for each sample point in a sample set is made, is an effective method. However, there is a problem that the calculation time for estimation of this regression is very long, because it is needed to use all kernel functions made for all sample points. In this paper, we propose an estimation method with a fast approximation by using a few selected kernel functions instead of all kernel functions. These kernel functions are those made for only sample points included in neighborhood with the point that we want to estimate for. By this estimation method with a fast approximation, we show that the calculation time for estimation is short, and the estimation accuracy for the proposed method does not degrade, compared to that for a conventional estimation method without approximation.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) crossover kernel / Nadaraya-Watson regression / neighborhood / approximate calculation
Paper # IBISML2018-46
Date of Issue 2018-10-29 (IBISML)

Conference Information
Committee IBISML
Conference Date 2018/11/5(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Hokkaido Citizens Activites Center (Kaderu 2.7)
Topics (in Japanese) (See Japanese page)
Topics (in English) Information-Based Induction Science Workshop (IBIS2018)
Chair Hisashi Kashima(Kyoto Univ.)
Vice Chair Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo)
Secretary Masashi Sugiyama(Nagoya Inst. of Tech.) / Koji Tsuda(AIST)
Assistant Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.)

Paper Information
Registration To Technical Committee on Infomation-Based Induction Sciences and Machine Learning
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Poster Presentation] A Fast Approximation of the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel
Sub Title (in English)
Keyword(1) crossover kernel
Keyword(2) Nadaraya-Watson regression
Keyword(3) neighborhood
Keyword(4) approximate calculation
1st Author's Name Toshio Ito
1st Author's Affiliation FUJITSU LABORATORIES LTD.(FUJITSU LAB)
2nd Author's Name Naoki Hamada
2nd Author's Affiliation FUJITSU LABORATORIES LTD.(FUJITSU LAB)
3rd Author's Name Kotaro Ohori
3rd Author's Affiliation FUJITSU LABORATORIES LTD.(FUJITSU LAB)
4th Author's Name Hiroyuki Higuchi
4th Author's Affiliation FUJITSU LABORATORIES LTD.(FUJITSU LAB)
Date 2018-11-05
Paper # IBISML2018-46
Volume (vol) vol.118
Number (no) IBISML-284
Page pp.pp.17-21(IBISML),
#Pages 5
Date of Issue 2018-10-29 (IBISML)