5 results for “SMOTE”
Research Article
Open Access A Comparative Evaluation of Interpolation and Generative Oversampling Techniques for Predictive Maintenance
Abdazeez Atere, Atere A, Hasan Kivrak, Kivrak H
International Symposium on AI-Driven Engineering Systems 2025 https://doi.org/10.36287/setsci.22.21.001
Predictive maintenance (PdM) enhances industrial operational efficiency by facilitating timely detection of equipment failures using machine learning models developed from historical maintenance data. Real-world industrial datasets frequently exhibit signific…
Research Article
Open Access Prediction of Recurrence of Differentiated Thyroid Cancer with Hybrid SMOTE-Stacking Model
Erkan Akkur, Akkur E, Serkan Cizmecioğulları, Cizmecioğulları S, Ahmet Cankat Öztürk, Öztürk A
International Trend of Tech Symposium 2024 https://doi.org/10.36287/setsci.21.6.033
Differentiated thyroid cancer (DTC) is the most frequent form of thyroid cancer. Although this type of cancer shows a favourable prognosis, the risk of recurrence remains a critical concern. Early and accurate prediction of the risk of recurrence is essential …
Research Article
Open Access Lightweight Attention-Based Framework for Semantic Segmentation and Compression of 3D LiDAR Data
Rytis Maskeliünas, Maskeliünas R, Sarmad Maqsood, Maqsood S
International Symposium on AI-Driven Engineering Systems 2025 https://doi.org/10.36287/setsci.22.5.001
Efficient semantic segmentation and compression of 3D point cloud data are essential for enabling scalable, real-world applications involving large-scale LiDAR environments. This work presents a lightweight hybrid framework that integrates point transformer v3…
Research Article
Open Access Forecasting Banking Desert Risk Using Branch Level and Merger Signals
Malavika Polanki, Polanki M
Proceedings of the International Conference on Open Finance (ICOF 2026) 2026 https://doi.org/10.36287/setsci.25.5.001
In the United States, banking desert status is classified annually from that same year’s branch data, producing a contemporaneous snapshot of current access rather than a forecast of which communities are likely to change status next. This study tests whether …
Research Article
Open Access XAI-Powered Comparative Diabetes Prediction with XGBoost, SVM and Artificial Neural Networks
Furkan Sefa Demirci, Demirci F, Remzi Yıldırım, Yıldırım R
International Symposium on AI-Driven Engineering Systems 2025 https://doi.org/10.36287/setsci.22.30.001
In this study, diabetes prediction was conducted using XGBoost, Support Vector Machines (SVM), and a Multilayer Artificial Neural Network (ANN). Attributes that cannot be biologically ‘0’ (e.g. glucose, BMI) were first marked as NaN. After filling the missing …
