Tahsin Shahnewaz

Jan 8, 2024 | mdpi.com | Nikolay Sirakov |Tahsin Shahnewaz |Arie Nakhmani |Nikolay Metodiev

1. IntroductionOne fundamental problem in the field of data classification with supervised machine learning (ML) is a shortage of or imbalanced training data [1,2,3]. For example, the training set of the public image database ISIC2020 [4] contains only 584 malignant images and approximately 33,126 benign images. Such a large class imbalance leads to overfitting [5], which impacts the prediction accuracy of a classifier.

Dec 12, 2023 | preprints.org | Arie Nakhmani |Tahsin Shahnewaz

Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 11 December 2023 / Approved: 12 December 2023 / Online: 12 December 2023 (07:24:28 CET) Sirakov, N.M.M.; Shahnewaz, T.; ---, A.N. Training Data Augmentation with Data Distilled by the Principal Component Analysis. Preprints 2023, 2023120821.