model_housing_price_data

Models Implemented

1. 1. Linear Regression

      1. Objective: Use linear regression to predict income based on home value and rent

      2. Why chosen: It may be a useful tool for users to gauge what kind of income they would need or expect to move to certain zipcodes in UT or CO. They can also use this data to compare to moving to other states regarding income in comparison to the housing cost. 

      3. Assumptions: Numeric data; 

      4. Hyperparameter tuning: N/A

   2. K-means Clustering

      1. Objective: Use clustering to group different zip codes by home and rent value

      2. Why chosen: Users may find similar zip codes regarding housing in CO and UT in relation to one another in terms of economics. They may also input certain income, rent, data from other states' zip codes and find similar zip codes in UT and CO.

      3. Assumptions: Numeric data, k=4

      4. Hyperparameter tuning: N/A