DeepCoreML 0.4.6

A collection of Machine Learning techniques for data management, engineering and augmentation.

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.