Prediction of Big Mart Sales Using Data Mining Techniques
In this research we have Big Mart Sales data from the Analytic Vidya Repository. The datascientists at Big Mart sales have collected 2013 sales from 1559 products across 10 stores in differentcities. In our study big mart salesdata are compared using various data mining techniques. We observed the accuracy of decisiontree is 81.037% accuracy of random forest is 97.66% & accuracy of support vector machine is 85.01% onthe basis of accuracy given by each model the random forest is best model of for prediction of sales andalso observed the relation between Item. MRP having highest correlation with our target variable & alsoobserved the data distributed around 64% of the item contains low fat while remaining contain regular fat.Her Our aim is to provided a prediction of sales using data mining techniques.
Authors
- Sharvari Jayavant Patil
Institutions
- Yashwantrao Chavan Maharashtra Open University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-02-14
- DOI
- https://doi.org/10.5281/zenodo.18639412
- Primary Topic
- Internet of Things and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00