Analysis of the lung cancer patient’s for data mining tool

Abstract

Data mining technology recently focuses on the methods of classification of the decision tree in data mining and propose a new algorithm for the classification of the decision tree with variable accuracy. The researcher uses the data analysis tool Rattle Rand Weka. The researcher use data sets for different age groups are divided into gender-related treatment for lung cancer using various modes of treatment in this research. The age group is in between (30-60 years) with categories in males and females. The decision tree is a suitable and sufficient algorithm for analyzing the results of treatment with radiation and chemotherapy for a specific age group. The Rattle R and Weka tools predict each group for best treatment method by which the appropriate treatment method can be analyzed. The predictions are also compared using graph plots with related tables also. These graphs are correlated with the forecasts. The researcher introduces the most efficient and widely used classification methods for data mining techniques and the main concepts of the decision tree method. In addition, the two data mining software rattle R and Weka are briefly described. To illustrate the procedure of this research, 200 real data sets were then compared in terms of the accuracy of the classification between the two different algorithms of the decision tree.