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July 8, 2019 07:03
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XGBoost with Python and Scikit-Learn
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
your code is goat
Small correction: under Command line parameters I think reg:logistic is meant for classification problems with probabilities and binary:logistic is for classification problems with only decision, not the other way around. Great notebook, cheers.
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Excellent case study!
I was only able to get an accuracy of about 93% with xgboost.