Publications by Christopher Bare
The Dream 8 Challenges
The 8th iteration of the DREAM Challenges are underway. DREAM is something like the Kaggle of computational biology with an open science bent. Participating teams apply machine learning and statistical modeling methods to biological problems, competing to achieve the best predictive accuracy. This year’s three challenges focus on reverse engine...
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Generate UUIDs in R
Here a snippet of R to generate a Version 4 UUID. Dunno why there wouldn’t be an official function for that in the standard libraries, but if there is, I couldn’t find it. ## Version 4 UUIDs have the form: ## xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx ## where x is any hexadecimal digit and ## y is one of 8, 9, A, or B ## f47ac10b-58cc-...
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Online class on Statistical Learning
Trevor Hastie and Robert Tibshirani are teaching an online class on Statistical Learning starting this week. The first week is introduction and overview, so it’s not too late to join up. They’ve also published a new book, An Introduction to Statistical Learning, as a more accessible companion to their widely revered The Elements of Statistica...
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Linear Models
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Regression with multiple predictors
Now that I'm ridiculously behind in the Stanford Online Statistical Learning class, I thought it would be fun to try to reproduce the figure on page 36 of the slides from chapter 3 or page 81 of the book. The result is a curvaceous surface that slices neatly through the data set. I’m not sure what incurable chemical imbalance explains why such ...
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Lee Edlefsen on Big Data in R
Lee Edlefsen, Chief Scientist at Revolution Analytics, spoke about Big Data in R at the FHCRC a week or two back. He introduced the PEMA or parallel external memory algorithm. “Parallel external memory algorithms (PEMA’s) allow solution of both capacity and speed problems, and can deal with distributed and streaming data.” When a problem i...
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