I've created a couple of models during some assignments and hackathons using algorithms such as Random Forest and XGBoost and used GridSearchCV to find the best combination of parameters. But what I'm not able to understand is how to select those parameters for GridSearchCV. I randomly put the parameters such as
params = {"max_depth" : [5, 7, 10, 15, 20, 25, 30, 40, 50,100],
"min_samples_leaf" : [5, 10, 15, 20, 40, 50, 100, 200, 500, 1000,10000],
"criterion": ["gini","entropy"],
"n_estimators" : [10, 15, 20, 40, 50, 75, 100,1000],
"max_features" : ["auto", "sqrt","log2"]}
But how do I decide if I could select better parameters which might be computationally better as well? I can't use the same above parameters for a Random Forest Classifier every single time surely?