A framework for data transformation in Credit Behavioral Scoring applications based on Model Driven Development
作者：
Highlights：
• A framework to systemize the data transformation in KDD projects is proposed.
• The framework reduces the time of transformation with automatic code generation.
• The framework improves the discriminant power of data mining techniques.
• The framework outperforms the two main frameworks in terms of accuracy.
• The framework is evaluated using a public database and a private database.
摘要
•A framework to systemize the data transformation in KDD projects is proposed.•The framework reduces the time of transformation with automatic code generation.•The framework improves the discriminant power of data mining techniques.•The framework outperforms the two main frameworks in terms of accuracy.•The framework is evaluated using a public database and a private database.
论文关键词：Data mining,Relational classification,Credit Behavioral Scoring,Model Driven Development,00-01,99-00
论文评审过程：Received 28 October 2015, Revised 6 February 2016, Accepted 28 October 2016, Available online 12 November 2016, Version of Record 2 January 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.059
