Function and surface approximation based on enhanced kernel regression for small sample sets
The function approximation problem is to find the appropriate relationship between a dependent and independent variable(s). Function approximation algorithms generally require sufficient samples to approximate a function. Insufficient samples may cause any function approximation algorithm to result...
Saved in:
Main Authors: | Shapiai, Mohd. Ibrahim, Ibrahim, Zuwairie, Khalid, Marzuki, Lee, Wen Jau, Pavlovic, Vladimir, Watada, Juilzo |
---|---|
Format: | Article |
Published: |
ICIC International
2011
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/29684/ http://www.ijicic.org/ijicic-10-06023.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhanced Nadaraya-Watson kernel regression: surface approximation for extremely small samples
by: Shapiai, Mohd. Ibrahim, et al.
Published: (2011) -
Enhanced nadaraya-watson kernel surface approximation for extremely small samples
by: Shapiai @ Abd. R., Mohd. Ibrahim, et al.
Published: (2011) -
Recipe generation from small samples: incorporating an improved weighted kernel regression with correlation factor
by: Shapiai, Mohd. Ibrahim, et al.
Published: (2011) -
Recipe generation from small samples by weighted kernel regression
by: Shapiai, Mohd. Ibrahim, et al.
Published: (2011) -
Enhanced kernel regression with prior knowledge in solving small sample problems
by: Shapiai, Mohd. Ibrahim, et al.
Published: (2011)