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Retail Store Sale Prediction

EasyChair Preprint no. 4803

7 pagesDate: December 25, 2020


In the following project, we have applied machine learning to a real world problem of predicting retail stores sales. Such predictions helps store managers in creating effective staff schedules that increase productivity. We used popular open source programming language Python and used its libraries like NumPy, scikit-learn, pandas , matplotlib for modelling, analysis and prediction and visualization. We have used different techniques like regression, ensemble and XGB regression. In view of nature of our problem, Root Mean Square Error (RMSE) is used to measure the prediction accuracy

Keyphrases: Ensemble, machine learning, NumPy, RMSE, scikit-learn, XGB regression

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Tanya Charan Pahadi and Palak Rani and Abhishek Verma},
  title = {Retail Store Sale Prediction},
  howpublished = {EasyChair Preprint no. 4803},

  year = {EasyChair, 2020}}
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