Metric Based Attribute Reduction Method in Dynamic Decision Tables
Feature selection is a vital problem which needs to be effectively solved in knowledge discovery in databases and pattern recognition due to two basic reasons: minimizing costs and accurately classifying data.
Janos Demetrovics +3 more
doaj +1 more source
Neighborhood Attribute Reduction: A Multicriterion Strategy Based on Sample Selection
In the rough-set field, the objective of attribute reduction is to regulate the variations of measures by reducing redundant data attributes. However, most of the previous concepts of attribute reductions were designed by one and only one measure, which ...
Yuan Gao +3 more
doaj +1 more source
Multi-objective attribute reduction in three-way decision-theoretic rough set model
Attribute reduction plays an important role in rough set theory. Many attribute reduction methods have been proposed based on different definitions of attribute reduct, while an attribute reduct can be regarded as a minimal attribute subset that ...
Wei-Wei Li +3 more
semanticscholar +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Generalized Discernibility Function Based Attribute Reduction in Incomplete Decision Systems [PDF]
A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table.
Dinh, Vu Van, Giang, Nguyen Long
core
Cost-sensitive approximate attribute reduction with three-way decisions
In the research spectrum of rough set, the task of attribute reduction is obtaining a minimal attribute subset that preserves certain properties of the original data.
Yu Fang, Fan Min
semanticscholar +1 more source
Design and analysis strategies for robust microbiome ageing research
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Ensemble Classification of Data Streams Based on Attribute Reduction and a Sliding Window
With the current increasing volume and dimensionality of data, traditional data classification algorithms are unable to satisfy the demands of practical classification applications of data streams. To deal with noise and concept drift in data streams, we
Yingchun Chen, Ou Li, Yu Sun, Fei Li
doaj +1 more source
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source

