Need help in building X G Boost Model in R



I have the data from May 2014 to April 2017. I want to predict no of applications in each store in each day of a month. So my target variable would be ‘Total Apps’.

I am kind of stuck how to divide the data into train and test and implement the model. I am new to R and also X G Boost. Can some one help me build a model in R to predict ‘Total Apps’ for the month of May 2017?



I am not able to understand your question. Do you want to know the different types of methods used to split a dataset into train and test or you wish to know some functions in R which can split a dataset into train and test to be able to apply XGBoost on it?




Thank you for responding to my question. I believe that we should split the date 70% into train and 30% into test.

However I’m not able to implement it because I think X G Boost Runs only if variables are either numeric or factors. And also I’ve read somewhere that we need to change the data frame to matrix before running the model.

Would you be able to connect to me and kind of go through the building of model and R script?

I have prepared the data and ready to build the model. I’m sure it’s not gonna take more than an hour or two.

I am ready to pay you for the support. This is my high priority task at work.




Please go through below articles which explain xgboost with code .

Once you have went through it, Please let me know if you still left with any questions.