Incorporating Ensembled Stacked Approach into Automated Machine Learning in an Attempt to Predict Acute Ischemic Heart Disease in Patients with Atypical Chest Pain: Secondary Analysis of a Single-Center Retrospective Cohort Study

Remanufacturability Evaluation Method for Used Vehicles Based on Stacking Ensemble Learning Framework

“…Stacking learning is an ensemble learning method combining multiple base learners and trains a meta-learner to obtain more accurate prediction results. This method has been proven successful in many fields, such as predicting plant soil moisture [24], evaluating slope stability [25], predicting acute ischemic heart disease in atypical chest pain patients [26], and detecting web-based attacks [27], etc. Due to the randomness, nonlinearity, and lack of sufficient data samples of remanufacturability [21], the accuracy of evaluating the remanufacturability is generally low.…”