Application of the pessimistic pruning to increase the accuracy of C4.5 algorithm in diagnosing chronic kidney disease

摘要: A technique to dig valuable information buried or hidden in data collection which is so big be found an interesting patterns that was previously unknown called mining. Data mining has been applied the healthcare industry. One used classification. The decision tree included classification of and algorithm developed by C4.5 algorithm. classifier designed using applying pessimistic pruning diagnosing chronic kidney disease. Pessimistic use identify remove branches are not needed, this done avoid overfitting generated In paper, result obtained these classifiers presented discussed. Using shows increase accuracy 1.5% from 95% 96.5%