Data mining process involves a number of steps from data collection to visualization identify useful massive set. the same time, recent advances machine learning (ML) and deep (DL) models can be utilized for effectual rainfall prediction. With this motivation, article develops novel comprehensive oppositional moth flame optimization with prediction (COMFO-DLRP) Technique. The proposed CMFO-DLRP...

In modern drug discovery, the combination of chemoinformatics and quantitative structure–activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling researchers to harness vast potential machine learning (ML) techniques for predictive molecular design analysis. This review delves into fundamental aspects chemoinformatics, elucidating intricate nature chemical data cruci...

Coreset selection, which aims to select a subset of the most informative training samples, is long-standing learning problem that can benefit many downstream tasks such as data-efficient learning, continual neural architecture search, active etc. However, existing coreset selection methods are not designed for deep may have high complexity and poor generalization performance. In addition, recen...