Local Separability Assessment: A Novel Feature Selection Method for Multimedia Applications

机译：局部可分性评估：多媒体应用中的一种新颖的特征选择方法

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摘要

Feature selection technology can help to reduce feature redundancy and improve classification performance. Most general feature selection methods do not perform well on high-dimension large-scale data sets of multimedia applications. In this paper we propose a novel feature selection method named Local Separability Assessment. We try to measure the separation level of samples in subregions of feature space, and integrate them for evaluating the separability of features. Our method has favorable performance on large-scale continuous data sets, and requires no priori hypothesis on data distribution. The experiments on various applications have proved its excellence.

机译：特征选择技术可以帮助减少特征冗余并提高分类性能。大多数通用特征选择方法在多媒体应用程序的高维大规模数据集上效果不佳。在本文中，我们提出了一种新的特征选择方法，称为局部可分性评估。我们尝试测量特征空间子区域中样本的分离水平，并将其集成以评估特征的可分离性。我们的方法在大规模连续数据集上具有良好的性能，并且不需要关于数据分布的先验假设。在各种应用上的实验证明了它的卓越性。

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来源
《Advances in Multimedia Information Processing - PCM 2008》|2008年|871-874|共4页
会议地点 Tainan(CT);eTainan(CT)
作者
Kun Tao; Shou-Xun Lin; Yong-Dong Zhang; Sheng Tang;
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作者单位

Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China Graduate School of the Chinese Academy of Sciences, Beijing, 100049, China;

Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China;

Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China;

Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类计算机网络;
关键词
local separability assessment; feature selection;

机译：本地可分离性评估；功能选择;

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专利

1. Feature subset selection for support vector machine through separability assessment in kernel-defined feature space [J] . Tang YH, Gao JH, Yang CX, Journal of computational and theoretical nanoscience . 2007,第7a8期

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2. Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea [J] . Jung Richard, Ehlers Manfred International journal of applied earth observation and geoinformation . 2016,第Null期

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3. FEATURE SELECTION BASED ON COMPACTNESS AND SEPARABILITY: COMPARISON WITH FILTER-BASED METHODS [J] . Chen Chien-Hsing Computational Intelligence . 2014,第3期

机译：基于紧凑性和可分离性的特征选择：与基于过滤器的方法比较
4. Local Separability Assessment: A Novel Feature Selection Method for Multimedia Applications [C] . Kun Tao, Shou-Xun Lin, Yong-Dong Zhang, Pacific Rim Conference on Multimedia . 2008

机译：本地可分离评估：多媒体应用的新颖特征选择方法
5. Algorithms for enhancing pattern separability, feature selection and incremental learning with applications to gas-sensing electronic nose systems. [D] . Polikar, Robi. 2000

机译：应用于气敏电子鼻系统的算法，用于增强模式可分离性，特征选择和增量学习。
6. Selection of Genetic and Phenotypic Features Associated with Inflammatory Status of Patients on Dialysis Using Relaxed Linear Separability Method [O] . Leon Bobrowski, Tomasz Łukaszuk, Bengt Lindholm, -1

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7. Algorithms for enhancing pattern separability, feature selection and incremental learning with applications to gas sensing electronic nose systems [O] . Polikar, Robi 2000

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8. Computerized Pattern Recognition Applications to Chemical Analysis. Development of Interactive Feature Selection Methods for the K-Nearest Neighbor Technique. [R] . pichler, marty a. perone,sam p. 1974

机译：计算机模式识别在化学分析中的应用。 K-最近邻技术交互特征选择方法的发展。

Local Separability Assessment: A Novel Feature Selection Method for Multimedia Applications

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