Non-numeric features generally have to be encoded into one or more numeric features before applying machine learning models. This article covers some of the different encoding techniques, the category_encoders package, and some of the pros and...
We know to split our data into a training and a testing set before we do our preprocessing, let alone our modeling. Often we are not as careful when doing cross-validation; we should really do things like scale our data within cross-validation...
The principles of Hadley Wickham's tidy data, and how it relates to long and wide form data.
We show how to take an Excel spreadsheet, with merged column headings, and process it for further analysis.
What does it mean for data to be in long form vs wide form, and when would you use each? In Pandas, how do you convert from one form to another?
One technique, sometimes called "target" or "impact" encoding, uses the average value of the target variable per value to encode. The James-Stein encoder is a twist the "shrinks" the target value back to the global average to stop statistical...