Feature selection for classification with Spearman's rank correlation coefficient-based self-information in divergence-based fuzzy rough sets
J Jiang, X Zhang, Z Yuan - Expert Systems with Applications, 2024 - Elsevier
Feature selection facilitates uncertainty disposal and information mining, and it has received
widespread research interests. Divergence-based fuzzy rough sets (Div-FRSs), a new kind …
widespread research interests. Divergence-based fuzzy rough sets (Div-FRSs), a new kind …
Feature selections based on three improved condition entropies and one new similarity degree in interval-valued decision systems
B Chen, X Zhang, J Yang - Engineering Applications of Artificial …, 2023 - Elsevier
Feature selections facilitate classification learning in various data environments. Aiming at
interval-valued decision systems (IVDSs), feature selections rely on information measures …
interval-valued decision systems (IVDSs), feature selections rely on information measures …
Confidence-Induced Granular Partial Label Feature Selection via Dependency and Similarity
Partial label learning (PLL) tackles scenarios where the unique ground-truth label of each
sample is concealed within a candidate label set. Dimensionality reduction, considering …
sample is concealed within a candidate label set. Dimensionality reduction, considering …
Tri-level attribute reduction based on neighborhood rough sets
Tri-level attribute reduction is an interesting topic that aims to reduce the data dimensionality
from different levels and granularity perspectives. However, existing research exhibits …
from different levels and granularity perspectives. However, existing research exhibits …
Semi-supervised feature selection with minimal redundancy based on group optimization strategy for multi-label data
D Qing, Y Zheng, W Zhang, W Ren, X Zeng… - … and Information Systems, 2024 - Springer
With the development of intelligence technology, high-dimensional multi-label data exist in
practical applications, which makes multi-label learning a significant challenge. Feature …
practical applications, which makes multi-label learning a significant challenge. Feature …
[HTML][HTML] Pipeline and Rotating Pump Condition Monitoring Based on Sound Vibration Feature-Level Fusion
Y Wan, S Lin, Y Gao - Machines, 2024 - mdpi.com
The rotating pump of pipelines are susceptible to damage based on extended operations in
a complex environment of high temperature and high pressure, which leads to abnormal …
a complex environment of high temperature and high pressure, which leads to abnormal …
K-Means Post-Training Optimizer
B Isikoglu, M Kubatova, A Cetin - 2024 Innovations in Intelligent …, 2024 - ieeexplore.ieee.org
We present a novel approach to optimize artificial intelligence (AI) models using
unsupervised learning, specifically utilizing the k-means clustering algorithm with varying …
unsupervised learning, specifically utilizing the k-means clustering algorithm with varying …