TY  - JOUR
AB  - Purpose For classification problems of customer relationship management (CRM), the purpose of this paper is to propose a method with interpretability of the classification results that combines multiple decision trees based on a genetic algorithm.Design/methodology/approach In the proposed method, multiple decision trees are combined in parallel. Subsequently, a genetic algorithm is used to optimize the weight matrix in the combination algorithm.Findings The method is applied to customer credit rating assessment and customer response behavior pattern recognition. The results demonstrate that compared to a single decision tree, the proposed combination method improves the predictive accuracy and optimizes the classification rules, while maintaining interpretability of the classification results.Originality/value The findings of this study contribute to research methodologies in CRM. It specifically focuses on a new method with interpretability by combining multiple decision trees based on genetic algorithms for customer classification.
VL  - 32
IS  - 5
SN  - 1355-5855
DO  - 10.1108/APJML-03-2019-0125
UR  - https://doi.org/10.1108/APJML-03-2019-0125
AU  - Zhang Zhe
AU  - Dai Yue
PY  - 2019
Y1  - 2019/01/01
TI  - Combination classification method for customer relationship management
T2  - Asia Pacific Journal of Marketing and Logistics
PB  - Emerald Publishing Limited
SP  - 1004
EP  - 1022
Y2  - 2024/04/19
ER  -