基于决策树(J48)分类算法的血液分析检测癌症

Oladosu Oyebisi Oladimeji, A. Oladimeji
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引用次数: 0

摘要

乳腺癌是世界上第二大死因。乳腺癌占全世界所有癌症死亡人数的16%。大多数检测乳腺癌的方法都非常昂贵和困难,比如乳房x光检查。本研究论文的目的是使用J48算法通过血液分析检测乳腺癌,该算法将作为这些昂贵方法的替代方案。采用J48算法对116个实例进行分类,并采用10倍交叉验证和保留过程,再加上随机种子的变化。交叉验证和保留程序的平均准确率分别为84.65%和89.99%。虽然也发现血糖水平是检测乳腺癌的主要决定因素,但它必须与其他属性结合起来才能做出其他健康问题(如糖尿病)的决定。
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Detecting breast cancer through blood analysis using decision tree (J48) classification algorithm
Breast cancer is the second major cause of death in the world. Breast cancer accounts for 16% of all cancer deaths worldwide. Most of the methods of detecting breast cancer very expensive and difficult such as mammography. The objective of this research paper is detecting breast cancer through blood analysis using J48 algorithm which will serve as alternative to these expensive methods. The J48 algorithm was used to classify 116 instances also,10-fold cross validation and holdout procedure were used coupled changing of random seed. Average accuracies of 84.65% and 89.99% were acquired for cross validation and holdout procedure. Although it was also discovered that Blood Glucose level is a major determinant in detecting breast cancer, it has to be combined with other attributes to make decision as a result of other health issues such as diabetes.
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