Articles by jmount

The Intercept Fallacy

September 7, 2020 | jmount

A common mis-understanding of linear regression and logistic regression is that the intercept is thought to encode the unconditional mean or the training data prevalence. This is easily seen to not be the case. Consider the following example in R. library(wrapr) We set up our example data. # build our […] [Read more...]

0.83 is a Special AUC

September 6, 2020 | jmount

0.83 (or more precisely 5/6) is a special Area Under the Curve (AUC), which we will show in this note. For a classification problem a good probability model has two important properties: The model is well calibrated. When the model says there is a p-probability of being in the class, […]
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New WVPlot: ROCPlotPairList

September 4, 2020 | jmount

We have a new R WVPlots plot: ROCPlotPairList. It is useful for comparing the ROC/AUC of multiple models on the same data set. library(WVPlots) set.seed(34903490) x1
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Free vtreat Tutorial Videos

July 17, 2020 | jmount

I would like to re-share links to our free vtreat data preparation system introduction videos, which show you what sort of machine learning problems vtreat can help you with. Python vtreat introduction video (PyData LA 2019), slides here. R vtreat introduction video (Why R? Foundation). The idea is: instead of […] [Read more...]

What is Chapter 8 of Practical Data Science with R?

June 9, 2020 | jmount

Chapter 8 “Advanced Data Preparation” of Practical Data Science with R is a study in: Using the R vtreat package for advanced data preparation. Cross-validated data preparation. It is the professionally edited, ready to cite version of an important data preparation methodology. An advantage being: a number of well documented […] [Read more...]
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