TY - JOUR AU - S.Mohana Saranya, S.Mohanapriya, PY - 2020/03/11 Y2 - 2024/03/29 TI - SALES PREDICTION USING MACHINE LEARNING ALGORITHM JF - International Journal of Advanced Science and Technology JA - IJAST VL - 29 IS - 3s SE - Articles DO - UR - http://sersc.org/journals/index.php/IJAST/article/view/5937 SP - 1049 - 1055 AB - Sales business can be made successful by predicting the sales in advance. Predicting market sales is the only way of quantitative measure of all potential deals by every people of the organizations selling the product in a given market. Sales prediction is important in business and it is the key factor of success in business. There are many advert ages of sales prediction. More success in the business can be achieved with the help of more accurate prediction of sales. Prediction helps in reducing inventory and to schedule customer’s orders. Prediction model can be accurately designed using Gradient Boost (GBT) algorithm to assess likely sales for many retailing organizations. The sales can be predicted based on a mixture of many features like previous sales information, information about shops, retail contenders, school and state vacations, location and shop accessibility. XG Boost improves model generalization. In XG Boost training is very fast than compared to Gradient boost and can be parallelized or distributed across clusters. ER -