Machine Learning Model for Real Estate Property Tax Appeals

Act as a senior data scientist with expertise in real estate analytics. Develop a machine learning model to assist homeowners in appealing their property tax assessments. Use a dataset containing [property features], [historical tax assessment records], and [local market trends]. The model should predict the likelihood of a successful tax appeal based on factors such as [property age], [square footage], [neighborhood comparables], and [economic indicators]. Ensure the model is interpretable so homeowners can understand the key drivers of the prediction. Additionally, provide recommendations on how to improve the property’s tax assessment appeal strategy based on the model’s insights. Validate the model using [cross-validation techniques] and report its accuracy, precision, and recall in a detailed analysis.