The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...

Native Python implementation. A native Python implementation for a variety of multi-label classification algorithms. To see the list of all supported classifiers, check this link. Interface to Meka. A ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

This research introduces an innovative approach to image classification, by making use of Vision Transformer (ViT) architecture. In fact, Vision Transformers (ViT) have emerged as a promising option ...

PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most ...

The complexity of fire and smoke in terms of shape, texture, and color presents significant challenges for accurate fire and smoke detection. To address this, a YOLOv8-based detection algorithm ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...