Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Fine-tuned DistilBERT model for binary sentiment classification (positive/negative) on review data, using Hugging Face Transformers with custom training and inference pipelines.

The shift is simple but significant. Chatbots gave us answers. Copilot Tasks aims to give us completed items from the to-do list. Microsoft is letting a small group try it today, with plans to bring ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.

Abstract: We consider a human-automation team jointly solving binary classification tasks over multiple time stages. At each stage, the automation observes the data for a batch of classification tasks ...