  The Brazilian government often misclassifies the goods it buys. That makes it
hard to audit government expenditures. We cannot know whether the price paid
for a ballpoint pen (code #7510) was reasonable if the pen was misclassified as
a technical drawing pen (code #6675) or as any other good. This paper shows how
we can use machine learning to reduce misclassification. I trained a support
vector machine (SVM) classifier that takes a product description as input and
returns the most likely category codes as output. I trained the classifier
using 20 million goods purchased by the Brazilian government between 1999-04-01
and 2015-04-02. In 83.3% of the cases the correct category code was one of the
three most likely category codes identified by the classifier. I used the
trained classifier to develop a web app that might help the government reduce
misclassification. I open sourced the code on GitHub; anyone can use and modify
it.
