When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual ...

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Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Predictive Analytics is a sophisticated forecasting system that relies on data mining, statistical modelling, and machine learning. It is an offshoot of advanced analytics that uses historical data to ...

Abstract: Electric vehicle (EV) technology is an emerging eco-friendly solution that has reshaped the transportation sector. This paper aims to design a controller for EV speed tracking using three ...

Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Overview: The Java ecosystem now offers a wide variety of ML frameworks - from lightweight toolkits for data mining to ...

This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Abstract: Random forest regression is a widely used machine learning algorithm. In this study, random forest regression is employed to predict groundwater levels. Five influencing factors are ...