Adaptive iterative clustering and decision tree for multimodal personal credit prediction

Yi Feng; Yiji Mao; Yilin Hu

doi:10.1117/12.2641274

4 August 2022 Adaptive iterative clustering and decision tree for multimodal personal credit prediction

Yi Feng, Yiji Mao, Yilin Hu

Proceedings Volume 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022); 123061K (2022) https://doi.org/10.1117/12.2641274
Event: Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 2022, Changchun, China

Abstract

With the rapid development of the personal credit market, it is accompanied by financial risks brought about by dishonesty. Among the existing personal credit prediction models, the traditional machine learning model is ineffective in dealing with multiple categories of users due to its poor generalization ability. In contrast, the neural network model requires many samples to cover multiple modal users. Its high training cost also makes this method limited. This paper proposes an adaptive iterative multimodal clustering method to predict the default of credit users. According to the multicategory characteristics of credit users, the method first divides users into multiple sets from coarse to fine-grained and then establishes decision tree models for prediction. This method not only solves the problem of the poor generalization ability of traditional machine learning models but also ensures that the overall training cost of the model is low. Comparative experiments are conducted based on representative credit datasets to verify the superiority and effectiveness of the proposed model. Experimental results show that the composite model outperforms other machine learning models and is suitable for personal credit loan prediction problems.

Citation Download Citation

Yi Feng, Yiji Mao, and Yilin Hu "Adaptive iterative clustering and decision tree for multimodal personal credit prediction", Proc. SPIE 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 123061K (4 August 2022); https://doi.org/10.1117/12.2641274

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KEYWORDS

Data modeling

Composites

Machine learning

Statistical modeling

Neural networks

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