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A method to analysis Prostate Cancer stages and treatments

机译:一种分析前列腺癌阶段和治疗方法的方法

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C4.5 decision tree construction algorithm is widely used in medical field. But this algorithm C4.5 does not perform efficiently for mass calculations. Hence, in this paper an effort has been made to combine K-means and apriori algorithm results as the inputs of C4.5 algorithm to get better result. This technique has been applied in synthesized “Prostate Cancer Datasets” and try to achieve a robust and reliable classification to discover proper stages and treatments for the prostate cancer. We use WEKA data mining tool for our experiment purpose.
机译:C4.5决策树建设算法广泛应用于医学领域。但该算法C4.5不会有效地进行质量计算。因此,在本文中,已经努力将K-Means和ApRiori算法结果与C4.5算法的输入组合起来,以获得更好的结果。该技术已应用于合成的“前列腺癌数据集”,并试图达到稳健且可靠的分类,以发现前列腺癌的适当阶段和治疗。我们使用Weka数据挖掘工具进行我们的实验目的。

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