The hyper-parameters used in the model are tuned using the Lagrange method. The terms a, a ∗ mentioned in Equation 4 denote the Lagrange multipliers and should satisfy the following equality: a j a j ...

This research is dedicated to assessing the effectiveness of machine learning and ensemble learning models in groundwater potential mapping in Morocco's Tan-Tan region. The Tan-Tan region serves as a ...

To develop a robust approach to conduct classification on data (a person is wearing glasses or not) using a ensemble of models, which include machine learning models (random forest,Gradient Boosting ...

Corporate distress signals are important for both institutions and banks when evaluating firms’ performances. This paper evaluates five different models in predicting the distress for listed companies ...

But machine learning models should be trained with sufficient data. As the TCAD simulation generated dataset is relatively small in size, performance of the model based on only one algorithm may yield ...

The metamodel is a set of support vector machine (SVM) algorithms that is used in the aggregation phase of the ensemble algorithm. Because there is uncertainty in measuring the growth rate via the ...

Machine Learning: Accelerating Predictive Modeling Although it’s popular to think of AI and machine learning as recent innovations, in fact both terms were coined in the 1950s.