A study on using Python vs Weka on dialysis data analysis

J. Mitrpanont, Wudhichart Sawangphol, Thanita Vithantirawat, Sinattaya Paengkaew, Prameyuda Suwannasing, Atthapan Daramas, Yi-Cheng Chen
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引用次数: 10

Abstract

Health data has been drastically increasing in capacity and variety. Due to large and complex collection of datasets, it is difficult to process data using traditional data processing techniques. Machine Learning techniques, such as KNN and Naïve Bayes, have been used. Python and Weka are tools that are widely used in the field of data analytics. Therefore, this paper gives the comprehensive comparison between both tools together with some machine learning algorithms on data analytic of Dialysis Dataset. The results show that using Python provides the better performance in term of correct/incorrect instances, precision, and recall.
使用Python和Weka进行透析数据分析的研究
卫生数据的容量和种类都在急剧增加。由于数据集的庞大和复杂,使用传统的数据处理技术很难处理数据。机器学习技术,如KNN和Naïve贝叶斯,已经被使用。Python和Weka是在数据分析领域广泛使用的工具。因此,本文对这两种工具进行了全面的比较,并对透析数据集的一些机器学习算法进行了分析。结果表明,在正确/错误实例、精度和召回率方面,使用Python提供了更好的性能。
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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