A nested stacking ensemble model for predicting districts with high and low maternal mortality ratio (MMR) in India

The ensemble is an efficacious machine learning framework that combines variety of algorithms for better performance and effective prediction. Over the past few years, numerous researchers proposed wide variety of ensemble methodologies in the field of healthcare industry. In the present research paper, a nested ensemble has been suggested based on Stacking and Voting schemes for prediction and analysis of Maternal Mortality Ratio (MMR) in India. The presented nested ensemble combines Base Learners and Meta Learners by employing different classification algorithms and prediction results were afterwards evaluated by using K-fold cross validation and thus, facilitating the statistical distribution of results. Further, the effectiveness of the ensemble was investigated by comparing its performance with the various single learning algorithms in terms of accuracy, precision, recall, F-measure and ROC.

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