This first started as a Decision Tree using the California Health Interview Survey (CHIS) 2020 to create a predictive model that will predict Depression in high school teenagers in California based on Poverty levels as well as a few other variables. A Neural Network was then built using the same data set, in order to compare the results between the two different types of algorithms.

The model does not work well. In the CHIS 2020 Depression is a low cardinality variable, and the number of of observations for those that were depressed is low. Neither model is able to identify those that are depressed because of this. This calls for either more data, or data augmentation.

This project was primarily done with Python and Keras.