使用Python预测癌症疾病的数据挖掘算法比较

Mehtab Mehdi, K. Pahwa, Bharti Sharma
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引用次数: 0

摘要

从根本上说,机器学习是数据科学的一部分,而数据科学就是人工智能。我们使用机器学习算法在分析过去的数据后预测未来的结果。这种数据处理技术被称为数据分析。机器学习算法分为三个部分:监督、无监督和强化。这些算法将在其他部分进一步细分。在本文中,我们比较了这些算法,以便将来我们可以很容易地更新机器学习算法的精度水平。为此,我们使用了上传到kaggle上的医疗保健数据。我们使用python编程语言实现了机器学习算法,并计算了每种算法的精度级别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Data Mining Algorithms for Predicting the Cancer Disease Using Python
Fundamentally, machine learning is the part of data science which is nothing but AI. We use machine learning algorithms for predicting the future results after analyzing the past data. This technique of data processing is called data analytics. Machine Learning algorithms are divided in three sections: Supervised, Unsupervised and Reinforcement. These algorithms are further subdivided in other sections. In this paper we are comparing these algorithms by which in future we could easily update the accuracy level of the ML algorithms. For doing this we used the healthcare data which has been uploaded on the kaggle. We implemented the machine learning algorithm using python programming language and calculated the accuracy level of each algorithm.
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