Linear regression, also called simple regression, is one of the most common techniques of regression analysis. Multiple regression is a broader class of regression analysis, which encompasses both ...

is a measure of the amount of multicollinearity in regression analysis. Multicollinearity exists when there is a correlation between multiple independent variables in a multiple regression model.

The financial sector is heavily data driven. Every day, trillions of data is generated by the global financial system; these ...

Tick populations have remained stable over the past two decades, but the percentage of ticks with dangerous pathogens has ...

This study provides a valuable extension of credibility-based learning research by showing how feedback reliability can distort reward-learning biases in a disinformation-like bandit task. Although ...

Higher Education, Sustainable Career Development, Sustainable Career Resistance to Change, Psychological Well-Being Share and Cite: Argyropoulou, K. , Karavia, A.S. and Chaidemenaki, O. (2025) ...

Then, six ML models with optimised hyperparameters including multiple linear regression, random forest regressor (RF ... We performed a waiting list analysis using all available data entries from the ...