TY - GEN
T1 - Prediction of sales value in online shopping using linear regression
AU - Gopalakrishnan, T.
AU - Choudhary, Ritesh
AU - Prasad, Sarada
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - The aim of this paper is to analyze the sales of a big superstore, and predict their future sales for helping them to increase their profits and make their brand even better and competitive as per the market trends by generating customer satisfaction as well. The technique used for prediction of sales is the Linear Regression Algorithm, which is a famous algorithm in the field of Machine Learning. The sales data is from the year 2011-13 and prediction of data for the year 2014 is done. Then, real-time data of the year 2014 is also taken and the actual data of the year 2014 has been compared to the predicted data to calculate the accuracy of prediction. This is done so as to validate our results with the actual ones. This in turn would help them take necessary actions (which has been discussed later) for their increase their sales.
AB - The aim of this paper is to analyze the sales of a big superstore, and predict their future sales for helping them to increase their profits and make their brand even better and competitive as per the market trends by generating customer satisfaction as well. The technique used for prediction of sales is the Linear Regression Algorithm, which is a famous algorithm in the field of Machine Learning. The sales data is from the year 2011-13 and prediction of data for the year 2014 is done. Then, real-time data of the year 2014 is also taken and the actual data of the year 2014 has been compared to the predicted data to calculate the accuracy of prediction. This is done so as to validate our results with the actual ones. This in turn would help them take necessary actions (which has been discussed later) for their increase their sales.
UR - https://www.scopus.com/pages/publications/85070381763
UR - https://www.scopus.com/pages/publications/85070381763#tab=citedBy
U2 - 10.1109/CCAA.2018.8777620
DO - 10.1109/CCAA.2018.8777620
M3 - Conference contribution
AN - SCOPUS:85070381763
T3 - 2018 4th International Conference on Computing Communication and Automation, ICCCA 2018
BT - 2018 4th International Conference on Computing Communication and Automation, ICCCA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Computing Communication and Automation, ICCCA 2018
Y2 - 14 December 2018 through 15 December 2018
ER -