Design and Implementation of Credit Evaluation System for Healthy Aged Service

摘要

As the problem of global aging intensifies, the quality of credit for healthy aged service has increasingly received more attention. The traditional evaluation of credit quality of healthy aged service still uses the manual entry way to evaluate the service quality, which cannot well deal with huge data in the evaluation for healthy aged service quality. Therefore, in this paper, a credit quality evaluation system is designed and implemented to predict and evaluate user's credit ratings by a standard operation flow for healthy aged service. In this system, we establish a predictive model to automatically evaluate healthy aged service credit quality by machine learning technique. The credit data is quantified and processed for extracting credit ratings-related features. Machine learning technique is utilized to explore the latent relationship between the credit data and its rating. The credit evaluation model for healthy aged service can be built by supervised learning method for predicting user's credit ratings. The design and implementation of this system provides a reasonable solution for auto-evaluation of credit quality of healthy aged service, which can save more manpower and improve service quality in healthy aged service.