摘要
机器学习算法利用数学和统计学方法从大量数据中学习和提取有用信息,能够为决策提供支持。数据分类旨在将数据分组到预定义的类别中,而标准化方法则涉及对数据进行格式化和规范化处理,以提高算法的效率和准确性。为增强机器学习在数据处理中的有效性和一致性,文章深入探讨了基于机器学习算法的数据分类与标准化方法。
Machine learning algorithms use mathematical and statistical methods to learn and extract useful information from large amounts of data,which can provide support for decision-making.Data classification aims to group data into predefined categories,while standardization involves formatting and normalizing data to improve algorithm efficiency and accuracy.To enhance the effectiveness and consistency of machine learning in data processing,this article delves into data classification and standardization methods based on machine learning algorithms.
作者
张豹
ZHANG Bao(The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing Jiangsu 210046,China)
出处
《信息与电脑》
2024年第6期53-55,共3页
Information & Computer
关键词
数据分类
机器学习算法
标准化
数据处理
data classification
machine learning algorithms
standardization
data processing