An Integrated machine learning and DEA-predefined performance outcome prediction framework with high-dimensional imbalanced data
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Publication:6148945
DOI10.1080/03155986.2023.2168943MaRDI QIDQ6148945
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Publication date: 8 February 2024
Published in: INFOR: Information Systems and Operational Research (Search for Journal in Brave)
performance evaluationdata envelopment analysismachine learningfeature selectioncontextual variables
Learning and adaptive systems in artificial intelligence (68T05) Management decision making, including multiple objectives (90B50)
Cites Work
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- Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
- Measuring the efficiency of decision making units
- Robustness against separation and outliers in logistic regression
- A survey of cross-validation procedures for model selection
- Evolution of bank efficiency in Brazil: a DEA approach
- Bankruptcy prediction using a data envelopment analysis.
- Robust support vector machines based on the rescaled hinge loss function
- Assessing bank efficiency and performance with operational research and artificial intelligence techniques: a survey
- Outliers and Residual Distributions in Logistic Regression
- The Application of Data Envelopment Analysis in Conjunction with Financial Ratios for Bank Performance Evaluation
- A Comparison of Data Envelopment Analysis and Artificial Neural Networks as Tools for Assessing the Efficiency of Decision Making Units
- Simulation Techniques in Operations Research—A Review
- The elements of statistical learning. Data mining, inference, and prediction
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