[HTML][HTML] Accelerator for supervised neighborhood based attribute reduction
In neighborhood rough set, radius is a key factor. Different radii may generate different
neighborhood relations for discriminating samples. Unfortunately, it is possible that two …
neighborhood relations for discriminating samples. Unfortunately, it is possible that two …
Quick attribute reduct algorithm for neighborhood rough set model
L Yong, H Wenliang, J Yunliang, Z Zhiyong - Information Sciences, 2014 - Elsevier
In this paper, we propose an efficient quick attribute reduct algorithm based on
neighborhood rough set model. In this algorithm we divide the objects (records) of the whole …
neighborhood rough set model. In this algorithm we divide the objects (records) of the whole …
Composite rough sets for dynamic data mining
As a soft computing tool, rough set theory has become a popular mathematical framework
for pattern recognition, data mining and knowledge discovery. It can only deal with attributes …
for pattern recognition, data mining and knowledge discovery. It can only deal with attributes …
Fuzzy neighborhood covering for three-way classification
Neighborhood Covering (NC) is the union of homogeneous neighborhoods and provides a
set-level approximation of data distribution. Because of the nonparametric property and the …
set-level approximation of data distribution. Because of the nonparametric property and the …
A deep fuzzy model for diagnosis of COVID-19 from CT images
From early 2020, a novel coronavirus disease pneumonia has shown a global “pandemic”
trend at an extremely fast speed. Due to the magnitude of its harm, it has become a major …
trend at an extremely fast speed. Due to the magnitude of its harm, it has become a major …
基于邻域粗糙集的多标记分类特征选择算法
段洁， 胡清华， 张灵均， 钱宇华， 李德玉 - 计算机研究与发展, 2015 - cqvip.com
多标记学习是一类复杂的决策任务, 同一个对象可能同时属于多个类别. 此类任务在文本分类,
图像识别, 基因功能分析等领域广泛存在. 多标记分类任务往往由高维特征描述 …
图像识别, 基因功能分析等领域广泛存在. 多标记分类任务往往由高维特征描述 …
Heterogeneous feature selection with multi-modal deep neural networks and sparse group lasso
L Zhao, Q Hu, W Wang - IEEE Transactions on Multimedia, 2015 - ieeexplore.ieee.org
Heterogeneous feature representations are widely used in machine learning and pattern
recognition, especially for multimedia analysis. The multi-modal, often also high …
recognition, especially for multimedia analysis. The multi-modal, often also high …
Improving green flexibility through advanced manufacturing technology investment: Modeling the decision process
Globalization and greening are two major trends manufacturing. Each trend has increased
organizational and supply chain risk and uncertainty. Advanced manufacturing technology …
organizational and supply chain risk and uncertainty. Advanced manufacturing technology …
An improved decision tree algorithm based on variable precision neighborhood similarity
C Liu, B Lin, J Lai, D Miao - Information Sciences, 2022 - Elsevier
The decision tree algorithm has been widely used in data mining and machine learning due
to its high accuracy, low computational cost and high interpretability. However, when dealing …
to its high accuracy, low computational cost and high interpretability. However, when dealing …
Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection
Third-party reverse logistics provider (3PRLP) selection plays an important role in the
operation and implemention of reverse logistics or reverse supply chains. Economic and …
operation and implemention of reverse logistics or reverse supply chains. Economic and …