Distributed boosting algorithm for classification of text documents

M. Sarnovský, Michal Vronc
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引用次数: 10

Abstract

Presented paper focuses on the area of analysis and classification of textual documents. We present the classification of documents based on boosting method applied on the decision tree algorithm. Main objective of the paper is to present the implementation of distributed boosting algorithm based on Map Reduce paradigm. We have used the GridGain framework as a platform for distributed data processing and have tested the implemented solution on two different dataset within our testing environment.
文本文档分类的分布式增强算法
本文主要研究文本文献的分析与分类。在决策树算法的基础上,提出了一种基于增强的文档分类方法。本文的主要目的是提出一种基于Map Reduce范式的分布式提升算法的实现。我们使用GridGain框架作为分布式数据处理的平台,并在我们的测试环境中在两个不同的数据集上测试了实现的解决方案。
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