Categories

Dec 31, 2019 in Data Science

Q:

Suppose we fit “Lasso Regression” to a data set, which has 100 features (X1,X2…X100).  Now, we rescale one of these feature by multiplying with 10 (say that feature is X1),  and then refit Lasso regression with the same regularization parameter.

Now, which of the following option will be correct?

A. It is more likely for X1 to be excluded from the model

B. It is more likely for X1 to be included in the model

C. Can’t say

D. None of these

1 Answer

Dec 31, 2019

Solution: B

Big feature values = smaller coefficients = less lasso penalty = more likely to have be kept

Click here to read more about Loan/Mortgage
Click here to read more about Insurance

Related questions

Madanswer
May 13 in Oracle
Jul 10 in Sql
Jan 21 in Data Science
...