Authors :
Keyaben patel; Navneet Kumar
Volume/Issue :
Volume 6 - 2021, Issue 9 - September
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3mcb7pS
Abstract :
The sales forecast is based on Big Mart sales
for various outlets to adjust the business model to
expected outcomes. The resulting data can then be used
to prediction potential sales volumes for retailers such as
Big Mart through various machine learning methods.
The estimate of the system proposed should take account
of price tag, outlet and outlet location. A number of
networks use the various machine- learning algorithms,
such as linear regression and decision tree algorithms,
and XGBoost regressor, which offers an efficient
prevision of Big Mart sales based on gradient. At last,
hyperparameter tuning is used to help you to choose
relevant hyperparameters that make the algorithm
Shine and produce the highest accuracy.
The sales forecast is based on Big Mart sales
for various outlets to adjust the business model to
expected outcomes. The resulting data can then be used
to prediction potential sales volumes for retailers such as
Big Mart through various machine learning methods.
The estimate of the system proposed should take account
of price tag, outlet and outlet location. A number of
networks use the various machine- learning algorithms,
such as linear regression and decision tree algorithms,
and XGBoost regressor, which offers an efficient
prevision of Big Mart sales based on gradient. At last,
hyperparameter tuning is used to help you to choose
relevant hyperparameters that make the algorithm
Shine and produce the highest accuracy.
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