An exploration in how discussion forum data can be used to measure faculty engagement and its effect on student outcomes
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Updated
Oct 10, 2018 - R
An exploration in how discussion forum data can be used to measure faculty engagement and its effect on student outcomes
an extremely basic Julia implementation of the Orthogonalizing EM (OEM) algorithm for penalized regression
Learning tasks with orthogonal/disjoint supports
An investigation into why on-ground students choose to take online equivalents of their in-person courses
Repo to keep track of work done in Dr. Robert McCulloch's Graduate Machine Learning course
A repository for a showcase project. I analyze juice consumer data, using logistic regression and logistic lasso penalized regression in R to predict what juice brand a customer purchases based on characteristics of the situation.
Multi-source sparse Tweedie modelling
Interactive Notebook demonstrating the R-library bigtime
Two applications of penalized models in statistical modeling
Bayesian regression with spike and slab prior. Inference with Gibbs sampling.
Penalized regression for multiple types of many features with missing data using expectation-maximization (EM) algorithm.
University of Utah—MKTG 6600: Business Algorithms | Taken: Fall 2020
GAUDI: a penalized regression based PRS method designed specifically for admixed individuals
Repo for the paper entitled "Developing Risk Prediction Models using Penalisation within Data that Adheres to Minimum Sample Size Criteria"
We explored various approaches to deal with high-dimensional data in this study, and we compared them using simulation and soil datasets. We discovered that grouping had a significant impact on model correctness and error reduction. For the core projection step, we first looked at the properties of all the algorithms and how they function to com…
Experiments for Binarsity: a penalization for one-hot encoded features
Raw files for a document providing an overview of mixed models from varying perspectives.
Flexible SVM framework implementation
An R package that implements the Hierarchical Feature Regression: a regularized group-shrinkage regression estimator based on supervised hierarchical graphs
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