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Novel Random Forest Methods And Algorithms For Autism Spectrum Disorders Research, Afrooz Jahedi
Novel Random Forest Methods And Algorithms For Autism Spectrum Disorders Research, Afrooz Jahedi
CGU Theses & Dissertations
Random Forest (RF) is a flexible, easy to use machine learning algorithm that was proposed by Leo Breiman in 2001 for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data. Its superior prediction accuracy has made it the most used algorithms in the machine learning field. In this dissertation, we use the random forest as the main building block for creating a proximity matrix for multivariate matching and diagnostic classification problems that are used for autism research (as an exemplary application). In observational studies, matching is used to optimize the balance …