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Epidemiology and Biostatistics Dissertation Defense: Melissa Meeker
Start Date: 5/8/2023Start Time: 2:00 PM
End Date: 5/8/2023End Time: 3:00 PM

Event Description

"A Spatial Extension of the Random Forest Algorithm"

Melissa Meeker, PhD student at Dornsife

The random forest machine learning algorithm is often used in spatial datasets with strong predictive performance. However, the random forest algorithm does not acknowledge the correlation structure in spatial datasets. In this dissertation, we propose three spatial extensions of the random forest which include (1) implementing a geographically stratified sampling approach, (2) incorporating a neighbor-based predictor set, and (3) modifying the split criterion used to produce the decision trees. We examine the effect of these modifications in three types of data: simulated data, Philadelphia Police Department investigations data, and Christiana Hospital NICU data.

Melissa Meeker is a PhD candidate in biostatistics at Drexel University with a B.S. in mathematics and computer science from Ursinus College. Melissa’s research interests include methods for spatial data, machine learning, and public health disparities.

Contact Information:
Name: Nancy Colon-Anderson
Email: nanderson@drexel.edu
Headshot of speaker
Nesbitt Hall, Room 751
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