A feature selection method based on multiple feature subsets extraction and result fusion for improving classification performance
J Liu, D Li, W Shan, S Liu - Applied Soft Computing, 2024 - Elsevier
Directly applying high-dimensional data to machine learning leads to dimensionality
disasters and may induce model overfitting. Feature selection can effectively reduce feature …
disasters and may induce model overfitting. Feature selection can effectively reduce feature …
A novel hybrid bat algorithm with a fast clustering-based hybridization
S Eskandari, MM Javidi - Evolutionary intelligence, 2020 - Springer
Bat algorithm (BA) is a new and promising metaheuristic search algorithm which could
outperform existing algorithms. However, BA can be easily trapped in a local optimum …
outperform existing algorithms. However, BA can be easily trapped in a local optimum …
CInf-FS: an efficient infinite feature selection method using K-means clustering to partition large feature spaces
SF Hassani Ziabari, S Eskandari, M Salahi - Pattern Analysis and …, 2023 - Springer
In this paper, we present a new feature selection algorithm for supervised problems. We
build our algorithm upon recently proposed infinite feature selection (Inf-FS) method where …
build our algorithm upon recently proposed infinite feature selection (Inf-FS) method where …
Streamwise feature selection on big data using noise resistant rough functional dependency
S Eskandari - Journal of Mathematical Modeling, 2021 - jmm.guilan.ac.ir
Online Streaming Features (OSF) is a data streaming scenario, in which the number of
instances is fixed while feature space grows with time. This paper presents a rough sets …
instances is fixed while feature space grows with time. This paper presents a rough sets …
[HTML][HTML] Online Streaming Feature Selection Using Geometric Series of the Adjacency Matrix of Features
S Eskandari - Signal and Data Processing, 2021 - jsdp.rcisp.ac.ir
Feature Selection (FS) is an important pre-processing step in machine learning and data
mining. All the traditional feature selection methods assume that the entire feature space is …
mining. All the traditional feature selection methods assume that the entire feature space is …
[引用][C] Analysis and Identification of Different Factors Affecting Students' Performance Using a Correlation-Based Network Approach
JCF Wong, TCY Yip - International Journal of Computer and Information …, 2021