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Data Mining Approach to Predict and Analyze the Cardiovascular Disease

机译:数据挖掘方法预测和分析心血管疾病

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This paper presents the experimental analysis of data provided by UCI machine learning repository. Weka open source machine learning tool provided by Waikato University reveals the hidden fact behind the datasets on applying supervised mathematical proven algorithm, i.e., J48 and Na?ve Bayes algorithm. J48 is an extension of ID3 algorithm having additional features like continuous attribute value ranges and derivation of rules. The data sets were analyzed using two approaches, i.e., first taken with selected attributes and taken with all attributes. The performance of both the algorithm reveals the accuracy of algorithm and predicting the various reasons behind this increasing problem of cardiovascular diseases.
机译:本文介绍了UCI机器学习存储库提供的数据的实验分析。 Weka Open Source Machine Learning工具提供的Waikato University提供的隐藏事实,在应用监督数学经过验证算法,即J48和NA贝雷斯算法上的应用程序集。 J48是ID3算法的扩展,其具有额外的特征,如连续属性值范围和规则的推导。 使用两种方法进行分析数据集,即首先使用选定属性并使用所有属性拍摄。 这两种算法的性能揭示了算法的准确性,并预测了这种增加的心血管疾病问题背后的各种原因。

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