Gradient Boosting Regressor Hyperparameter Optimization

[BerkayAkar]

Hi Dear Form users

ı have a questions. ı want to make a prediction by using gradient boosting Trees Regressor. So ı have a problem

parameters={

        "learning_rate":[0.1,0.01,0.001],  

        "n_estimators":range(100,1200,100),

       }

this is my hyperparameters

what should ı do ı m new to knime platform

[kienerj]

Duplicating question-

Please make use of the provided help in that thread to get you started. The node description of the parameter optimization loop node and the examples in your other thread should explain exactly what you need to do.

[BerkayAkar]

you are rigth but ı dont have any idea for node options

for example What is the counterpart of m-estimators in the node setting

[kienerj]

[BerkayAkar]

thanks fır giving advice but ı didn’t see pramaeter on options and ı talk about Gradient Bossting Regressoon

[kienerj]

Same applies. It’s right there in the node description.

[BerkayAkar]

no tge GBR node dosent gave Boosting options coldu you give me a workflow sample ?

[Daniel_Weikert]

number of estimators for boosting should be the number of trees which can be set in the variable settings
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