Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set

Access is limited to UniMAP community.

Saved in:
Bibliographic Details
Main Author: Nur Amalina, Ilyas
Other Authors: Dr. Yasmin Mohd Yacob
Format: Learning Object
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2016
Subjects:
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41891
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-41891
record_format dspace
spelling my.unimap-418912016-06-07T07:17:29Z Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set Nur Amalina, Ilyas Dr. Yasmin Mohd Yacob Gastritis Symmetrical uncertainty Algorithms Endoscopic Gastritis Data analysis Access is limited to UniMAP community. Classifying high dimensional numerical data is an exceptionally difficult issue. High dimensional data for example data sets with hundreds or thousands of features, can contain high degree of irrelevant and redundant information which greatly degrades the performance of learning algorithms. Therefore, feature selection becomes necessary for machine learning tasks for facing high dimensional data. To address this issue, an efficient feature selection method using symmetrical uncertainty is used to facilitate classifying high-dimensional numerical data. The focus here is on feature selection method that are able to assess the goodness or ranking of the individual features. The threshold method used here helps to accurately determine which features is relevant and which features is redundant. The relevant features is called as the essential features while the irrelevant features will be ignore from feature classification. 2016-06-07T07:17:29Z 2016-06-07T07:17:29Z 2015-06 Learning Object http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41891 en Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Gastritis
Symmetrical uncertainty
Algorithms
Endoscopic Gastritis
Data analysis
spellingShingle Gastritis
Symmetrical uncertainty
Algorithms
Endoscopic Gastritis
Data analysis
Nur Amalina, Ilyas
Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
description Access is limited to UniMAP community.
author2 Dr. Yasmin Mohd Yacob
author_facet Dr. Yasmin Mohd Yacob
Nur Amalina, Ilyas
format Learning Object
author Nur Amalina, Ilyas
author_sort Nur Amalina, Ilyas
title Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
title_short Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
title_full Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
title_fullStr Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
title_full_unstemmed Symmetrical uncertainty method to extract essential features for Endoscopic Gastritis data set
title_sort symmetrical uncertainty method to extract essential features for endoscopic gastritis data set
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2016
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41891
_version_ 1643799843376726016
score 13.214268