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Oversampling techniques for imbalanced data in regression
Published 2024“…<p>Our study addresses the challenge of imbalanced regression data in Machine Learning (ML) by introducing tailored methods for different data structures. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…We demonstrated the applicability of feature engineering techniques such as data imputation, transformation (e.g., scaling, centering, etc.), and data balancing using several case studies and the proposed semi-automated framework. …”
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A Survey of Data Clustering Techniques
Published 2023“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. …”
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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security
Published 2024“…We evaluated and cross validated the proposed techniques with current benchmarks. Consequently, the proposed hybrid deep learning anomaly detection approaches not only enhance IoT security but also provide a robust control system for addressing emerging multivariate cyber threats.…”
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Genetic biomarkers and machine learning techniques for predicting diabetes: systematic review
Published 2024“…Most studies focused on classical machine learning models, with SNPs being the most used data type, followed by gene expression profiles, while lipidomic and metabolomic data were the least utilized. …”
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Using XAI Techniques to Detect Targeted Data Poisoning Attacks on Healthcare Applications of Machine Learning Systems
Published 2025“…This research study explores the application of Explainable Artificial Intelligence (XAI) methods for detecting targeted data poisoning attacks in healthcare machine learning systems. …”
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Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique
Published 2021“…Data fusion has recently attracted much attention for energy efficiency in buildings, where numerous types of information may be processed. …”
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Multimodal Learning Techniques for Time Series Forecasting in Renewable Energy Systems: A Comprehensive Survey
Published 2025“…The growing availability of heterogeneous and complementary data modalities including meteorological forecasts, satellite imagery, numerical sensor streams, and grid interaction logs has motivated the application of multimodal learning techniques to improve time series forecasting accuracy. …”
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