标准化数据模型在机器学习中的应用研究  

Research on the Application of Standardized Data Models in Machine Learning

作　　者：杨颖[1] YANG Ying(Changjiang Polytechnic)

机构地区：[1]长江职业学院

出　　处：《中国标准化》2025年第6期39-41,共3页China Standardization

摘　　要：随着机器学习技术的广泛应用,数据标准化处理对模型性能的影响日益凸显。本研究构建了标准化数据处理模型,融合多种标准化方法,引入机器学习算法,建立了涵盖数据预处理、特征工程、模型训练的标准化应用框架。实验验证结果显示,采用标准化数据模型后,模型准确率提升15%、训练时间减少30%,且在不同应用场景中具有较强的适应性。标准化数据模型为机器学习应用提供了重要的数据基础支撑,对提升人工智能技术水平具有重要意义。With the wide application of machine learning technology,the impact of data standardization on model performance has become increasingly prominent.In this paper,a standardized data processing model is constructed,a variety of standardized methods are integrated,machine learning algorithms are introduced,and a standardized application framework covering data preprocessing,feature engineering,and model training is established.The experimental verification results show that the accuracy of the model is increased by 15%,the training time is reduced by 30%,and the model has strong adaptability in different application scenarios.Standardized data models provide important data foundation support for machine learning application,which are of great significance for improving the level of artificial intelligence technology.

关 键 词：数据标准化 机器学习 特征工程 模型性能 数据预处理 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]