A Comparative Study on Machine Classification Model in Lung Cancer Cases Analysis

摘要

Due to the differences of machine classification models in the application of medical data, this paper selected different classification methods to study lung cancer data collected from HIS system with experimental analysis, applying the R language on decision tree algorithm, Bagging algorithm, Adaboost algorithm, SVM, KNN and neural network algorithm for lung cancer data analysis, in order to explore the advantages and disadvantages of each machine classification algorithm. The results confirmed that in lung cancer data research, Adaboost algorithm and neural network algorithm have relatively high accuracy, with a good diagnostic performance.