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Found 3 papers, 0 papers with code
A framework for predicting, interpreting, and improving Learning Outcomes
We develop an Embibe Score Quotient model (ESQ) to predict test scores based on observed academic, behavioral and test-taking features of a student.
Selecting Biomarkers for building optimal treatment selection rules using Kernel Machines
Optimal biomarker combinations for treatment-selection can be derived by minimizing total burden to the population caused by the targeted disease and its treatment.
Feature Elimination in Kernel Machines in moderately high dimensions
We develop an approach for feature elimination in statistical learning with kernel machines, based on recursive elimination of features. We present theoretical properties of this method and show that it is uniformly consistent in finding the correct feature space under certain generalized assumptions. We present four case studies to show that the assumptions are met in most practical situations and present simulation results to demonstrate performance of the proposed approach.
