the predictive performance of Gradient Boosting with decision trees as base learners to model the claim frequency and the …. The out-of-sample performance measure results show that the predictive performance of the Gradient Boosting Model (GBM) is …

The study's objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic … Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a … Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a …

The primary objective in building predictive analytics models is to achieve optimal accuracy with real datasets. The … predictive analytics, focusing on expanding the storage capacity of the Discrete Hopfield Neural Network (DHNN). First, this …

technical trading rules over up to 66 years. Using a state-of-the-art test for superior predictive ability to control for data …

financial time series data. Findings - The results showed that the convertible bond price had a strong predictive power for low …