A method to analysis Prostate Cancer stages and treatments

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.