Data Classification of Hospital Information System Combining Improved FsO and Fuzzy Decision Tree
With the growing number of patients,the data in the hospital information system are also expanding,and effective data mining is the key to the effective diagnosis of doctors.Based on this,IFsO-FDT is obtained by proposing an improved bubble sort files by time(FsO)algorithm and fusing fuzzy decision tree(FDT)in the actual classification,and its performance and effectiveness are verified in practice.The experimental results show that the IFsO-FDT has better performance compared with other classification models,with the highest accuracy of 98.14％.It performs well in four data sets,among which it is more suitable for breast cancer data sets,with classification accuracy of more than 90％.The adaptability and generalization a-bility are the highest which are 0.80 and 1.03.In a word,IFsO-FDT has higher classification accuracy,and has great applica-tion value in actual hospital information system data classification.
IFsO algorithmfuzzy decision treehospital information dataclassification model
万方数据
维普
