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Probability based Extended Direct Attribute Prediction

by Manju, Ankit Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 5
Year of Publication: 2016
Authors: Manju, Ankit Kumar
10.5120/ijca2016912319

Manju, Ankit Kumar . Probability based Extended Direct Attribute Prediction. International Journal of Computer Applications. 155, 5 ( Dec 2016), 41-44. DOI=10.5120/ijca2016912319

@article{ 10.5120/ijca2016912319,
author = { Manju, Ankit Kumar },
title = { Probability based Extended Direct Attribute Prediction },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 5 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number5/26604-2016912319/ },
doi = { 10.5120/ijca2016912319 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:30.539422+05:30
%A Manju
%A Ankit Kumar
%T Probability based Extended Direct Attribute Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 5
%P 41-44
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper studies the object recognition along with the direct and indirect attribute prediction. The direct attribute prediction technique has been extended by using the probability based formulae. Moreover, information gain is also used to classify the object into different categories. The information gain is determined by using the entropy. The implementation of the work and comparison with existing DAP technique over YAHOO and pascal dataset signifies the effectiveness of the work.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Dap Iap Probability Sensitivity Specificity.

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