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              <text>Optimal allocation algorithm of marketing resources based on improved random forest</text>
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              <text>allocation algorithm; Improved random forest; marketing; resource optimization</text>
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              <text>Random Forest algorithm is an ensemble learning algorithm that classifies data by combining multiple decision trees. It has a wide range of applications and is not easy to overfit. It has a wide range of applications in medicine, bioinformatics, management and other fields. By studying the Cobb-Douglas sales function, it is found that it can only analyze the static allocation of marketing resources, but cannot describe the dynamic changes. Enterprise marketing resource management runs through the enterprise management from beginning to end. The research on marketing resource management is helpful for enterprises to grasp and control the whole process of marketing resource management from the overall and overall level, and has important theoretical value and reality for enterprise marketing management activities. significance. In the vast majority of enterprises in our country, the size of advertising promotion expenses and the number of salesmen is often determined based on the experience and subjective assumptions of decision makers, so it is difficult to say that they are optimized. This paper starts with determining the optimal advertising budget and the number of salespeople, and conducts applied research on the optimal allocation of marketing resources.  2023 IEEE.</text>
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              <text>Winster Praveenraj D.D.; Hussein L.; Tomar R.S.; Margarat G.S.; Vimala M.; Krishnaraj V.</text>
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              <text>2023 2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023, pp. 809-813.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/SmartTechCon57526.2023.10391496" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/SmartTechCon57526.2023.10391496&lt;/a&gt;
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              <text>ISBN: 979-835030541-8</text>
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              <text>Winster Praveenraj D.D., School of Business and Management, Christ (Deemed to be University), Bangalore, India; Hussein L., College of Technical Engineering, The Islamic University, Najaf, Iraq; Tomar R.S., Department of Computer Science &amp;amp; Engineering, IES College Of Technology, MP, Bhopal, 462044, India; Margarat G.S., New Prince Shri Bhavani College Of Engineering And Technology, India; Vimala M., Department of Electronics and Communication Engineering, P.S.R Engineering College, Tamilnadu, India; Krishnaraj V., Department of Mathematics, Sona College of Technology, Tamilnadu, Salem, India</text>
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