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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 6 | Month- June 2024
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Paper Title
Predictive Sales Analytics for Variable Timeframes using Multiple Machine Learning Models
Authors
Rushikesh Shinde, Rafe Shamsi, Pratham Nanaware, Savita Lohiya
Keywords
Predictive analytics, Sales forecasting, XGBoost, Random Forest, Linear Regression, LSTM, Variable timeframes, Streamlit.
Abstract
Predicting future sales accurately is crucial for businesses to optimize inventory management, plan marketing strategies, and enhance overall profitability. In this paper, we propose a comprehensive analysis of predictive sales analytics for variable timeframes utilizing machine learning models, specifically XGBoost, Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) networks. Through empirical evaluation and comparative analysis, we demonstrate the efficacy of XGBoost in forecasting sales for different timeframes, namely daily, weekly, and monthly. Our findings highlight the superior performance of XGBoost in terms of accuracy and robustness, making it an ideal choice for businesses seeking reliable sales predictions across diverse temporal scales.
IJCRT's Publication Details
Unique Identification Number - IJCRT2406219
Paper ID - 262860
Page Number(s) - c20-c27
Pubished in - Volume 12 | Issue 6 | June 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Rushikesh Shinde, Rafe Shamsi, Pratham Nanaware, Savita Lohiya, "Predictive Sales Analytics for Variable Timeframes using Multiple Machine Learning Models", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 6, pp.c20-c27, June 2024, Available at :http://www.ijcrt.org/papers/IJCRT2406219.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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