Sales Estimator Using Machine Learning Algorithm

Abstract

Today incorporation of estimation and decision analysis is required by analytical systems. Predicting the item sales is a very tough challenge so the business organization depends on the predictions of sales trends. Accuracy obtained in sales predictions serves as a boon to business organizations. Machine learning algorithms are efficient and effective for extracting hidden information from a huge dataset to enhance efficiency and accuracy of sales prediction. The detailed study and analysis of predictive models is used to perform future sales predictions. The problem with traditional prediction systems is that they are tough to deal with the enormous dataset in order to provide the accurate prediction. To overcome these challenges various machine learning techniques and algorithms can be used. On the basis of their performance, the model which gives more accuracy will be used to predict forecasting trends. The results obtained are encapsulated collectively in terms of accuracy, reliability and efficiency of the techniques that are used for forecasting and prediction.