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 there are hundreds of other features that have a clear correlation to the sell price (amount of people who attend the open house, crime, proximity to busy street, etc.) that I'm not including. I guess the problem is, there's not any money in having an accurate prediction.
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 there are hundreds of other features that have a clear correlation to the sell price (amount of people who attend the open house, crime, proximity to busy street, etc.) that I'm not including. I guess the problem is, there's not any money in having an accurate prediction.