Analysis and Prediction of Homelessness in the USA
- Reduced dimensions of a 380-features dataset by 96% through Exploratory Data Analysis (data cleaning, data visualization, feature selection).
- Built predictive models for homelessness rate with multivariate linear regression and random forest (RMSE 0.35 and 0.18).
