Forecasting Restaurant Inspection Failures

David Smith writes about an R model which predicts which restaurants are more likely to fail inspection:

Chicago’s Department of Public Health used the R language to build and deploy the model, and made the code available as an open source project on GitHub. The reasons given are twofold:

An open source approach helps build a foundation for other models attempting to forecast violations at food establishments. The analytic code is written in R, an open source, widely-known programming language for statisticians. There is no need for expensive software licenses to view and run this code.

Read on for more details and check out their GitHub repo.

Related Posts

CSV Import Speeds With H2O

WenSui Liu benchmarks three CSV loading methods in R: The importFile() function in H2O is extremely efficient due to the parallel reading. The benchmark comparison below shows that it is comparable to the read.df() in SparkR and significantly faster than the generic read.csv(). I’d wonder if there are cases where this would vary significantly; regardless, […]

Read More

Linear Prediction Confidence Region Flare-Out

John Cook explains why the confidence region of a tracked object flares out instead of looking conical (or some other shape): Suppose you’re tracking some object based on its initial position x0 and initial velocity v0. The initial position and initial velocity are estimated from normal distributions with standard deviations σx and σv. (To keep […]

Read More


December 2016
« Nov Jan »