Multigranulation rough sets: from partition to covering
G Lin, J Liang, Y Qian - Information Sciences, 2013 - Elsevier
The classical multigranulation rough set (MGRS) theory offers a formal theoretical framework
for solving the complex problem under multigranulation environment. However, it is …
for solving the complex problem under multigranulation environment. However, it is …
Neighborhood rough sets based multi-label classification for automatic image annotation
Automatic image annotation is concerned with the task of assigning one or more semantic
concepts to a given image. It is a typical multi-label classification problem. This paper …
concepts to a given image. It is a typical multi-label classification problem. This paper …
Neighborhood effective information ratio for hybrid feature subset evaluation and selection
W Zhu, G Si, Y Zhang, J Wang - Neurocomputing, 2013 - Elsevier
Feature selection has been widely discussed as an important preprocessing step in
machine learning and data mining. Evaluation criterion designing arises as a main aspect …
machine learning and data mining. Evaluation criterion designing arises as a main aspect …
Test‐cost‐sensitive attribute reduction of data with normal distribution measurement errors
The measurement error with normal distribution is universal in applications. Generally,
smaller measurement error requires better instrument and higher test cost. In decision …
smaller measurement error requires better instrument and higher test cost. In decision …
A Universal neighbourhood rough sets model for knowledge discovering from incomplete heterogeneous data
S Jing, K She, S Ali - Expert Systems, 2013 - Wiley Online Library
Neighbourhood rough set theory has proven already, as an efficient tool for knowledge
discovering from heterogeneous data. However, some types of the data are incomplete and …
discovering from heterogeneous data. However, some types of the data are incomplete and …
Plar: Parallel large-scale attribute reduction on cloud systems
Attribute reduction for big data is viewed as an important preprocessing step in the areas of
pattern recognition, machine learning and data mining. In this paper, a novel parallel …
pattern recognition, machine learning and data mining. In this paper, a novel parallel …
From principal curves to granular principal curves
H Zhang, W Pedrycz, D Miao… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
Principal curves arising as an essential construct in dimensionality reduction and data
analysis have recently attracted much attention from theoretical as well as practical …
analysis have recently attracted much attention from theoretical as well as practical …
优势关系决策信息系统的属性约简
刘晓峰， 王丽丽 - 吉林大学学报(信息科学版), 2013 - xuebao.jlu.edu.cn
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Exploring neighborhood structures with neighborhood rough sets in classification learning
We introduce neighborhoods of samples to granulate the universe and use the
neighborhood granules to approximate classification, thus they derived a model of …
neighborhood granules to approximate classification, thus they derived a model of …
Selecting key features for remote sensing classification by using decision-theoretic rough set model
F Xie, D Chen, J Meligrana, Y Lin… - … Engineering & Remote …, 2013 - ingentaconnect.com
There are many spectral bands or band functions developed for land-cover feature
measurements. When the ratio of the number of training samples to the number of feature …
measurements. When the ratio of the number of training samples to the number of feature …