|Table of Contents|

Improved Adaptive Ordinal Regression LearningBased on Locality Structure Preserving(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2019年02期
Page:
9-16
Research Field:
·数学与计算机科学·
Publishing date:

Info

Title:
Improved Adaptive Ordinal Regression LearningBased on Locality Structure Preserving
Author(s):
Wang Peng; Lü Jing; Shen Huale
School of Computer Science and Technology,Nanjing Normal University,Nanjing 210046,China
Keywords:
image classification; ordinal regression; structure preserving; fuzzy adaptive
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2019.02.002
Abstract:
The ordinal regression learning is a kind of machine learning which preserves the order relations between data. It is widely used in image classification and other fields. Usually,there is some prior knowledge in the ordinal regression model,but the local structure information is not considered. Exploring such information can help to improve the effectiveness of classifiers. In this paper,we propose an improved adaptive ordinal regression method which is based on locality preserving structure(SaLSP-LDLOR),and the newly developed method considers embedding the spatial distance measurement information of the image. Experimental results with the standard data sets verify the effectiveness and the robustness of the proposed method.

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Last Update: 2019-06-30