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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Supervised Sparse Learning With Applications In Bioinformatics, Kin Ming Puk
Supervised Sparse Learning With Applications In Bioinformatics, Kin Ming Puk
Industrial, Manufacturing, and Systems Engineering Dissertations
In machine learning and mathematical optimization, sparse learning is the use of mathematical norms such as L1-norm, group norm and L21-norm in order to seek a trade-off between the goodness-of-fit measure and sparsity of the result. Sparsity of result leads to a parsimonious learning model - in other words, only few features from the data matrix are required to build the learning model and for further interpretation. The motivations of employing sparse learning in bioinformatics are two-fold: firstly, a parsimonious learning model enhances the explanatory power; and secondly, a parsimonious model generally allows better prediction and generalizes better to new …
Ensemble Machine Learning To Predict Family Consent For Organ Donation, Md Ehsan Khan
Ensemble Machine Learning To Predict Family Consent For Organ Donation, Md Ehsan Khan
Graduate Dissertations and Theses
There is ever increasing disparity between number of organs needed for transplantation and numbers available for donation to save lives. As a result, thousands of people die every year waiting for organs. Therefore, it is now more important than ever before to take serious actions to decrease this disparity. One way to bridge gap between organ demand and supply is to increase family consent for organ donation. This research studied the factors associated with family consent. Machine Learning approach had been used in very few literature to understand factors related to family consent. This study uses six Ensemble Machine Learning …