Analysis of Various Classification Methods

Vidushi, Manisha Agarwal, Rekha Rajoria
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引用次数: 4

Abstract

The process of gaining knowledge from enormous amount of data is called data mining. This paper uses the Weka tool to compare different types of classification methods. Decision tree, Multilayer perceptron, Naïve Bayes, J48 algorithms are used for classification analysis in terms of correctly and incorrectly classified instances and Area of ROC curve. Test option selected is cross validation with 10 folds. Datasets used breast cancer, diabetes from health care industry. In health care industry huge data is available but not so much knowledge extracted.
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各种分类方法分析
从海量数据中获取知识的过程被称为数据挖掘。本文使用Weka工具对不同类型的分类方法进行比较。使用决策树、多层感知器、Naïve贝叶斯、J48算法对分类实例的正确和错误分类以及ROC曲线的面积进行分类分析。选择的测试选项是10次交叉验证。数据集使用了来自医疗保健行业的乳腺癌、糖尿病。在医疗保健行业有大量的数据,但没有那么多的知识被提取出来。
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