通过机器学习技术进行分析:调查

R. Reddy, G. Shyam
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引用次数: 3

摘要

分析和搜索客户购买数据中有意义的关联被认为是数据挖掘技术的最佳应用。机器学习是模仿智能的基本性质。机器从过去的信息中学习,以提高智能程序的性能。我们考虑无监督机器学习技术来分析各种类型的数据。使用的技术有聚类、特征提取和分类。机器学习主要用于展示准确的估计。本文的主要目的是介绍机器学习的概况,并讨论各种应用的无监督机器学习技术。此外,本文回顾了不同的机器学习技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis Through Machine Learning Techniques: A Survey
Analysis and search for meaningful associations in customer purchase data are considered as best applications of data mining techniques. Machine learning is the fundamental nature of imitation of intelligence. The machine learns from the past information to improve the performance of intelligent programs. We consider unsupervised machine learning techniques to analyze various sort of the data. Techniques used are clustering, feature extraction and classification. Machine learning is mainly employed to exhibit accurate estimate. The major objective of this paper is to present the outline of machine learning and discuss unsupervised machine-learning techniques for various applications. Further, this paper reviews the different machine learning techniques.
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