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Quantitative Issues in Cancer Research Working Seminar
March 30 @ 1:00 pm - 1:50 pm
Maya RamchandranDoctoral Student, Department of Biostatistics, Harvard University”A Clustered Cross-validation Weighted Generalization of Random Forest”ABSTRACT: This project considers extending the general multi-study ensembling framework proposed by Parmigiani and Patel (2017) to single datasets, with Random Forest as the learner. Specifically, we look at using clustering algorithms to first split a dataset into regions that maximize feature-effect heterogeneity across clusters and minimize it within. We then train Random Forest learners on each cluster, and then ensemble them using replicability weights. We then explore in which settings this method outperforms training a single Forest on the full dataset and how it compares to learners trained using the oracle clusters. Going forward, starting with the March 23 meeting, please download and import the following iCalendar (.ics) files to your calendar system.Weekly: https://harvard.zoom.us/meeting/uJMoc–qqjwvdL4F-POulE_jlE5PLZqL6w/ics?icsToken=98tyKuyvqz8sGNCStVz9f6kqW8H8b_H2lHVi_oUQrDDwDwVsaA_TY9JuCKNTRs-BIf you wish to join the meeting, you may request a passcode from the working group organizer, Dr. Jill Lundell (firstname.lastname@example.org).Join Zoom meetinghttps://harvard.zoom.us/j/575462475Join by telephone (use either number to dial in)+1 929 436 2866+1 669 900 6833International numbers available: https://harvard.zoom.us/u/abmuvT28sOne tap mobile: +19294362866,,575462475# US (New York)Join by SIP conference room systemMeeting ID: 575 462 email@example.com