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Distributed Feature Selection in Large n and Large p Regression Problems
Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets ...
Nonlinear Prediction in Credit Forecasting and Cloud Computing Deployment Optimization
This thesis presents data analysis and methodology for two prediction problems. The first problem is forecasting midlife credit ratings from personality information collected during early adulthood. The second problem is ...
Gaussian Process-Based Models for Clinical Time Series in Healthcare
Clinical prediction models offer the ability to help physicians make better data-driven decisions that can improve patient outcomes. Given the wealth of data available with the widespread adoption of electronic health records, ...