A study on forecasting bigmart sales using optimized machine learning techniques

Kumar, N. M. Saravana; Hariprasath, K.; Kaviyavarshini, N.; Kavinya, A.

doi:10.31763/sitech.v1i2.167

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…In this article Yi Yang et al [20] suggests a e-SVR to forecast Chinese tobacco sales for a certain time period in the future. It also includes a representation of the sale trend in N. M. Saravana Kumar et al [22] presents projected future sales in this research using data mining methods. Naive Bayes, Adaboost, Decision Tree with Naive Bayes, Particle Swarm Optimization, and Random Forest for prediction of sales are the algorithms that are compared.…”

Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts

ilyas¹,

Ikram²,

Butt³

et al. 2023

JICET

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Abstract— Sales predictions or forecasting can help in analyzing the current and future sales trends of a big mart company. Based on the sales prediction or forecast, a retailer company can plan its production, marketing and promotional activities. Using several machine learning techniques, the obtained data may then be utilized to predict possible sales for retailers. This paper investigates that which machine learning regression algorithm best predicts big marts sales and which technique has the highest correlation coefficient value and the lowest values of mean absolute error (MAE), relative absolute error (RAE), root mean squared error (RMSE), and root relative squared error (RRSE). A comparative analysis of various machine learning regression algorithms such as SMO regression, simple linear regression, linear regression, additive regression, multi-layer perceptron, random forest, and M5P will be provided in this paper. After the experiments are completed, a comparison of various cross validations and splitting ratios for training and testing data will be given.

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Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts

ilyas¹,

Ikram²,

Butt³

et al. 2023

JICET

View full text Add to dashboard Cite

show abstract

“…The catBoost model performs better than the linear regression and support vector regression models. [18] Uses both the time series models and the machine learning models for sales prediction in the automobile industry. The model is trained and tested with data that contains yearly, quarterly, and monthly features.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Study of Data Analytic Techniques for Sales Forecasting

2023

Recent Trends in Data Science and Its Applications

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Predicting the sales of a product or demand for a service is an utmost need in any industry. With the changes and increase in the channels and modes through which the products are sold, the prediction of sales in the future becomes tedious. The number of features that would help in predicting sales differs and increases. This leads to the usage of Machine Learning and Deep Learning Models in sales forecasting. A deep survey of various works that employ machine learning and Deep learning approaches for sales prediction is done and inferences are made. Every work studied has a list of models which are used as baseline models for comparison and the same is listed for better inferences. Works that address the problem of predicting the sales of new products are also discussed. A list of publicly available sales forecasting datasets is also given.

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Survey of Machine Learning and Deep Learning Approaches on Sales Forecasting

Dharshini

Vijila

2021

2021 4th International Conference on Computing and Communications Technologies (ICCCT)

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A study on forecasting bigmart sales using optimized machine learning techniques

Cited by 4 publications

References 16 publications

Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts

Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts

A Comprehensive Study of Data Analytic Techniques for Sales Forecasting

Survey of Machine Learning and Deep Learning Approaches on Sales Forecasting

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