overfitting. This paper aims at devising an algorithm that can carry the task of variable selection in the presence of a large … the number of zero claims. The resulting algorithm is assessed by measuring the out-of-sample AUC (Area Under the Curve …), a Machine Learning tool for quantifying predictive power. Finally, the application of the algorithm is demonstrated by …

the predictions. The technological risk is assessed through the transparency of the algorithm and the latency of the ML …

Expectation maximization (EM) algorithm is a popular and powerful mathematical method for parameter estimation in case …

This work presents a potent multiobjective multiverse algorithm to solve the highly complicated dynamic economic … the thermal stations. A novel algorithm is proposed where the dynamic economic dispatch problem with losses is converted … during each hour of the dispatch period. The proposed algorithm is first tested on five and ten thermal unit systems with B …

algorithm herself, her equity preference has no effect on the training procedure. So long as the data, however biased, contain … signal, they will be used and the learning algorithm will be the same. Equity preferences alone provide no reason to alter …