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Many enterprises face data quality issues such as missing data, data errors, data inconsistencies, etc. Using data mining algorithms to analyze and predict market data has become an important way for enterprises to improve their competitiveness and market efficiency. This article adopts data mining algorithms, uses large-scale market data for analysis and modeling, and constructs a data set containing multiple characteristic variables by collecting and sorting historical market data. This article chooses data mining algorithms to train and model the data set, and optimizes the performance and accuracy of the model by repeatedly adjusting model parameters and evaluation indicators. Research results show that the algorithm's accuracy test data is between 85% and 94%. By using algorithms for data analysis, companies can more accurately predict market trends, customer behavior and sales performance. This helps companies develop more precise marketing strategies and resource allocation plans, and improve marketing effectiveness and return rates.
Jiao et al. (Fri,) studied this question.
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