A survey on data mining classification algorithms

S. Umadevi, K. S. J. Marseline
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引用次数: 56

Abstract

Data mining refers to extracting or mining knowledge from large amount of data. It is also defined as finding hidden information from a database. It is a technique which is used primarily for discovering unknown patterns and that converts raw data into user understandable information. Nowadays it is being increasingly used in science and technology to extract the vast amount of data. Classification is the separating the given data according to their characteristics similar to one another. These are some of the classification methods Naïve Bayes Classifier, Decision tree, Neural Networks, and Support Vector Machine.
数据挖掘分类算法综述
数据挖掘是指从大量数据中提取或挖掘知识。它也被定义为从数据库中查找隐藏信息。这是一种主要用于发现未知模式并将原始数据转换为用户可理解信息的技术。如今,它在科学技术中越来越多地用于提取大量数据。分类是将给定的数据根据它们彼此相似的特征进行分离。这些是一些分类方法Naïve贝叶斯分类器,决策树,神经网络和支持向量机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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