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0

$begingroup$

I am building a model to predict, say house prices. Within my data I have sales and rentals. The Y variable is the price of either the sales or rentals. I also have a number of X variables to predict Y, such as number of bedrooms, bathrooms, meters squared etc.

I believe that the model will firstly make a split on the variable "sales" vs "rentals" as this would reduce the loss function - RMSE - the most.

Do you think it is best to train 2 models one for "sales" and the other for "rentals"? The RMSE for the model is quite high and this is in part due to the incorrect "Sales" predictions.

machine-learning xgboost

share|improve this question

asked yesterday

user113156user113156

1437

$endgroup$

add a comment | 

0

$begingroup$

I am building a model to predict, say house prices. Within my data I have sales and rentals. The Y variable is the price of either the sales or rentals. I also have a number of X variables to predict Y, such as number of bedrooms, bathrooms, meters squared etc.

I believe that the model will firstly make a split on the variable "sales" vs "rentals" as this would reduce the loss function - RMSE - the most.

Do you think it is best to train 2 models one for "sales" and the other for "rentals"? The RMSE for the model is quite high and this is in part due to the incorrect "Sales" predictions.

machine-learning xgboost

share|improve this question

asked yesterday

user113156user113156

1437

$endgroup$

add a comment | 

$begingroup$

I am building a model to predict, say house prices. Within my data I have sales and rentals. The Y variable is the price of either the sales or rentals. I also have a number of X variables to predict Y, such as number of bedrooms, bathrooms, meters squared etc.

I believe that the model will firstly make a split on the variable "sales" vs "rentals" as this would reduce the loss function - RMSE - the most.

Do you think it is best to train 2 models one for "sales" and the other for "rentals"? The RMSE for the model is quite high and this is in part due to the incorrect "Sales" predictions.

machine-learning xgboost

share|improve this question

asked yesterday

user113156user113156

1437

$endgroup$

share|improve this question

asked yesterday

user113156user113156

1437

share|improve this question

asked yesterday

user113156user113156

1437

asked yesterday

user113156user113156

1437

asked yesterday

user113156user113156

1437