You would think real estate would prove to be one of the few real life fields where machine learning would be able to predict the prices pretty accurately. You have: 1. List price 2. "Favorites" on the MLS. 3. Square footage 4. Bedrooms 5. Bathrooms 6. Sold price for nearby properties 7. Sold price for nearby properties relative to their list price And the list goes on... Is it that difficult to predict? Literally th…
If you want to try it, there are a few data sets kicking around, including a) https://www.kaggle.com/c/house-prices-advanced-regression-te... b) http://www.bis.org/statistics/pp_detailed.htm c) https://archive.ics.uci.edu/ml/datasets/housing If you had a really great model, you might be able to make some money with it--find underpriced (per the model) houses, buy them, and then try to sell them at the model's price.
So the whole idea of "comparable sales" is shaky.