Automate a Real Estate Investment Analysis for a Portfolio of Properties

Given a dataset of 100+ properties, including real estate market information, property characteristics, and sales history, develop an automated real estate investment analysis model. Consider using machine learning algorithms to classify properties as high-risk, medium-risk, or low-risk investments based on factors such as property type, location, and historical sales data. Evaluate the model's performance using metrics such as accuracy, precision, and recall. Provide recommendations for actionable steps investors can take to optimize their portfolio and minimize risk. Assume the given dataset has been pre-processed and is in a pandas dataframe format. As of 2026-05-20, provide a detailed analysis of the model's performance and its implications for real estate investment strategy.