Learning_rate=1 vs CV=2

Module 3. Hyperparameter tuning Manual tuning
#1

In the exercise M3.01
we have: lr = [0.01, 0.1, 1, 10]
and scores = cross_val_score(model, data_train, target_train, cv=2)
How can the score be computed when lr=1 if the cv=2?

#2

Hi @Luz_Mary,
lr is for Learning_Rate : the parameter that controls the ability of a new tree to correct the error of the previous sequence of trees and cv is in how many part you ll split your data to cross validate your model. So here your data will be splited in 2 to test your models with 4 different learning_rate argument and each of them will be crossvalidated.

#3

Thanks for your answer .
I really don’t understand the effect of “lr” .
Could you give me some bibliography for understanding it

#4

Hi @Luz_Mary, perhaps this link will help you to understand better the learning rate.