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

An ANN model offers the most accurate and reliable prediction of bubble-point pressure for Rmelan crude oils. For practical ...

New AI models are underperforming on SEO tasks. Discover why accuracy is down and how to adapt before these regressions ...

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 ...

Shrinking governing boards, diversifying beyond alumni and business executives, and mandating free speech vetting in leadership hires could reverse the chill on free speech and equip trustees to ...

Vorasidenib significantly reduced tumor growth rates in IDH1/2-mutant grade 2 glioma, improving PFS and TTNI compared to ...

Step selection functions are a useful tool for analysing fine-scale human movements to understand environmental interactions in the context of infectious disease epidemiology.

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

ABSTRACT: In this work, we seek the relationship between the order of the polynomial model and the number of knots and intervals that we need to fit the splines regression model. Regression models ...

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...

The majority of research predicted heating demand using linear regression models, but they did not give current building features enough context. Model problems such as Multicollinearity need to be ...