Hello everyone!
I´m building a real-estate price predictor with a dataset from a selling website (
Properati Data ) (
Property price predictions: Great Buenos Aires(N) )
I filtered the data, dealt with missing and categorical columns and then got to train a a couple models (a random forest and then a gradient booster). The random forest performed better, with an error of about 60k USD, I am trying to tweak a couple things in order to reduce this error...
Can anyone help me to reduce it? Give me any advice?
Thanks
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[Marco] [Sánchez Sorondo]
[UBA]
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