DeepCoreML is a collection of Machine Learning techniques for data management, engineering, and augmentation. More specifically, DeepCoreML includes modules for:
- Data management
- Text data preprocessing
- Text representation, vectorization, embeddings
- Dimensionality reduction
- Generative modeling
- Imbalanced datasets
Licence: Apache License, 2.0 (Apache-2.0)
Dependencies:NumPy, Pandas, Matplotlib, Seaborn, joblib, Synthetic Data Vault (SDV), pyTorch,scikit-learn, xgboost, imblearn, Reversible Data Transforms (RDT), tqdm.
GitHub repository: https://github.com/lakritidis/DeepCoreML
Publications:
- L. Akritidis, P. Bozanis, "A Clustering-Based Resampling Technique with Cluster Structure Analysis forSoftware Defect Detection in Imbalanced Datasets", Information Sciences, vol. 674, pp. 120724, 2024.
- L. Akritidis, A. Fevgas, M. Alamaniotis, P. Bozanis, "Conditional Data Synthesis with Deep Generative Models for Imbalanced Dataset Oversampling", In Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 444-451, 2023, 2023.
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