## Pass the estimator obtained after fitting to scoring function as a parameter

Suppose I want to do a RandomizedSearchCV with custom both estimator and scorer :

Suppose I want to do a RandomizedSearchCV with custom both estimator and scorer :

When I use the following code with Data matrix `X`

of size (952,144) and output vector `y`

of size (952), `mean_squared_error`

metric returns negative values, which is unexpected. Do you have any idea?

I have a dataset, which has previously been split into 3 sets: train, validation and test. These sets have to be used as given in order to compare the performance across different algorithms.