使用机器学习模型预测和分析肺癌

Yapeng Chen
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引用次数: 0

摘要

肺癌是最严重的癌症之一,死亡率很高。在大量研究中,研究人员发现,预防肺癌对对抗它的人更有效。本文旨在预测检测个体患肺癌的可能性,并探讨其主要影响因素。我们应用了三种机器学习模型,包括线性回归。多项式回归和自举法用于此任务。在实验中。我们发现线性回归达到了最好的性能,MSE最低(0.11)。此外,我们发现年龄、吸烟和饮酒在肺癌发生中起重要作用。为肺癌的预防提供了全面的预测和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction and analysis of lung cancer using machine learning models
Lung cancer is one of the most serious cancers, which has high death rate. In much research, researchers find that preventing lung cancer more effective for people to against it. In this paper, we aim to predict the possibility of lung cancer for the test individuals and exploit the main factors. We apply three machine learning models, including linear regression. Polynomial regression and bootstrap for this task. In the experiment. We find the linear regression achieves the best performance, with the lowest MSE (0.11). Furthermore, we find that the age, smoke and alcohol take important role in lung cancer. The author provides a comprehensive prediction and analysis for lung cancer precaution.
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