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Sales Prediction System Using Machine Learning

EasyChair Preprint no. 3243

8 pagesDate: April 23, 2020


The objective is to perform techniques like Clustering Model and measures for sales predictions. On the basis of a performance evaluation, a best suited predictive model is suggested for the company sales trend forecast. The results are summarized in terms of  accuracy of machine learning techniques taken for prediction . The main objective of the system is to analyze the future sales of a particular company and to predict whether a particular sales will increase or decrease by using different machine learning algorithms like – Random Forest just one commodity is meaningless to sellers. A general prediction for all commodities is needed.Data mining is a discipline that can be used to gather information by data classifier,  Decision Tree, and Linear Regression.

Keyphrases: Decision Tree, linear regression, predictive model, Random Forest, Sales

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mansi Panjwani and Rahul Ramrakhiani and Hitesh Jumnani and Krishna Zanwar and Rupali Hande},
  title = {Sales Prediction System Using Machine Learning},
  howpublished = {EasyChair Preprint no. 3243},

  year = {EasyChair, 2020}}
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