When linear regression
algorithm is used in MLTK
, the field called coefficient
is returned by the summary
command.
Is this value a Partial regression coefficient?
Or Standard Partial regression coefficient?
If the former is correct, I think that because the dimensions of each variable are different (price, distance, percentage, etc.), the magnitude of those values is unreliable and I can't know which variable is important.
If anyone knows about it, please tell me.
We are returning the coefficients provided by scikit-learn, specifically the .coef_ attribute, as documented here:
http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html
You can inspect the code directly in the MLTK directory under ml-spl/bin/algos/LinearRegression.py
We are returning the coefficients provided by scikit-learn, specifically the .coef_ attribute, as documented here:
http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html
You can inspect the code directly in the MLTK directory under ml-spl/bin/algos/LinearRegression.py
Thank you for answer.
Since the command summary
seems to get the attribute of coef as it is from sklearn, the field coefficient
seems to be a partial regression coefficient not standard partial regression coefficient as far as I checked ml-spl/bin/algos/LinearRegression.py
and sklearn
.