[HTML][HTML] A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016
In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …
[HTML][HTML] Feature selection using joint mutual information maximisation
Feature selection is used in many application areas relevant to expert and intelligent
systems, such as data mining and machine learning, image processing, anomaly detection …
systems, such as data mining and machine learning, image processing, anomaly detection …
A feature selection method via analysis of relevance, redundancy, and interaction
L Wang, S Jiang, S Jiang - Expert Systems with Applications, 2021 - Elsevier
Feature selection aims at selecting important features that can enhance learning
performance in data mining, pattern recognition, and machine learning. Filter feature …
performance in data mining, pattern recognition, and machine learning. Filter feature …
Credit risk assessment mechanism of personal auto loan based on PSO-XGBoost Model
C Rao, Y Liu, M Goh - Complex & Intelligent Systems, 2023 - Springer
As online P2P loans in automotive financing grows, there is a need to manage and control
the credit risk of the personal auto loans. In this paper, the personal auto loans data sets on …
the credit risk of the personal auto loans. In this paper, the personal auto loans data sets on …
A novel feature-based SHM assessment and predication approach for robust evaluation of damage data diagnosis systems
Abstract Structural Health Monitoring (SHM) involves periodic recording and analysis in
buildings and infrastructure prone to face external forces, ambient vibration, or natural …
buildings and infrastructure prone to face external forces, ambient vibration, or natural …
A survey for study of feature selection based on mutual information
X Su, F Liu - 2018 9th workshop on hyperspectral image and …, 2018 - ieeexplore.ieee.org
Feature selection is a hot topic in information science to deal with high-dimensional data. In
this paper, feature selection method are classified from the perspective of evaluation …
this paper, feature selection method are classified from the perspective of evaluation …
Feature assessment and ranking for classification with nonlinear sparse representation and approximate dependence analysis
Feature selection has received significant attention in knowledge management and decision
support systems in the past decades. In this study, kernel-based sparse representation and …
support systems in the past decades. In this study, kernel-based sparse representation and …
Temperature effects on low cycle fatigue deformation of powder metallurgy superalloy FGH95
The macroscopic morphology and microstructure evolution mechanism of the FGH95 alloy
were investigated with regard to fracture under low-cycle fatigue at different temperatures …
were investigated with regard to fracture under low-cycle fatigue at different temperatures …
Feature selection from high dimensional data based on iterative qualitative mutual information
High Dimensional cancer microarray is devilishly challenging while finding the best features
for classification. In this paper a new algorithm is proposed based on iterative qualitative …
for classification. In this paper a new algorithm is proposed based on iterative qualitative …
[PDF][PDF] Feature Engineering Methods in Intrusion Detection System: A Performance Evaluation
F Zare, P Mahmoudi-Nasr - International Journal of Engineering …, 2023 - researchgate.net
Today, the number of cyber-attacks has increased and become more complex with an
increase in the size of high-dimensional data, which includes noisy and irrelevant features …
increase in the size of high-dimensional data, which includes noisy and irrelevant features …