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Based on the real data of a Chinese commercial bank's credit card, in this paper, we classify the credit card customers into four classifications by K-means. Then we built forecasting models separately based on four data mining methods such as C5.0, neural network, chi-squared automatic interaction detector, and classification and regression tree according to the background information of the credit...
This paper applies a generalized regression neural network (GRNN) for predicting the friction coefficient of deposited Cr1-xAlxC films on high-speed steel substrates via direct current (DC) magnetron sputtering systems. The Cr1-xAlxC films exhibited some excellent characteristics, such as low friction coefficient, high hardness, and large contact angle. In this study, a GRNN model is applied for predicting...
In this paper, neural network based ensemble learning methods are introduced in predicting activities of COX-2 inhibitors in Chinese medicine quantitative structure-activity relationship (QSAR) research. Three different ensemble learning methods: bagging, boosting and random subspace are tested using neural networks as basic regression rules. Experiments show that all three methods, especially boosting,...
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