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July 8, 2019 07:03
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XGBoost with Python and Scikit-Learn
From the Feature Importance graph, Delicassen has the highest F score. Doesn't this mean that Delicassen was the most important feature as opposed to Grocery which was fourth best?
No answer to malambomutila comment?
Excellent case study!
I was only able to get an accuracy of about 93% with xgboost.
Thanks a lot
I like how you described each parameter meaning I had no idea you could use Drop out using D.A.R.T
From the Feature Importance graph, Delicassen has the highest F score. Doesn't this mean that Delicassen was the most important feature as opposed to Grocery which was fourth best?
yes u are right @malambomutila
nice work
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-Nice. It is helpful to run in Jupyter Notebook. Thank you