Classifciation of Items in School Budgets with a Logistic Regression Model

School budgets in the United States are incredibly complex, and there are no standards for reporting how money is spent. Schools want to be able to measure their performance--for example, are we spending more on textbooks than our neighboring schools, and is that investment worthwhile? However to do this comparison takes hundreds of hours each year in which analysts hand-categorize each line-item. The goal of this project is to build a machine learning algorithm that can automate that process.