Learning And Optimization Of The Kernel Functions From Insufficiently Labeled Data
Amongst all the machine learning techniques, kernel methods are increasingly becoming popular due to their efficiency, accuracy and ability to handle high-dimensional data. The fundamental problem related to these learning techniques is the selection of the kernel function. Therefore, learning th...
Saved in:
Main Author: | Abbasnejad, M. Ehsan |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2010
|
Subjects: | |
Online Access: | http://eprints.usm.my/41234/1/M._Ehsan_Abbasnejad-shahfiq.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An optimized framework for header suppression of real time IPV6 traffic in multiprotocol label switching (MPLS) networks.
by: Mohammed, Imad Jasim
Published: (2011) -
Finding Best Semantic Relatedness Functions For Schema Matchers
by: Emadzadeh, Ehsan
Published: (2010) -
Spatial Kernel-based Generalized C-mean Clustering for Medical Image Segmentation.
by: Lee, Song Yeow
Published: (2010) -
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
by: Mohammed, Alhassan Afnan
Published: (2022) -
A Data Grid Replica Management System With
Local And Global Multi-Objective Optimization
by: E. Almistarihi, Husni Hamad
Published: (2009)