The present study utilized various regression fitting models, including BP neural network, decision tree analysis, random forest method, and SVM regression analysis, among others, to compare and determine the optimal fitting method for the data.

Multiple parameters were used to describe the economic characteristics of the region, and data processing techniques were applied to the sailboat prices to remove outliers at the same parameter level.

Following data preprocessing, correlation analysis was conducted, and parameters with weak correlations were omitted to simplify the model's complexity and enhance its descriptive capability for the samples.

英文翻译具有学术风格多用高级词汇不要漏翻译:本研究采用的数据的回归拟合模型种类多样化包括BP神经网络决策树分析法randomforest方法和svm回归分析法等五种方法并比较得出最优拟合方法。 	在描述地区经济特征时使用了多个参数同时针对帆船价格进行数据处理删除了相同参数水平下的异常值。 	在预处理数据后进行相关性分析并将参数精简化省略相关性不大的参数简化了模型的复杂度的同时也兼具对样本的描述

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