Fig. 15
From: A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks
The FCM MSE. There are some clustering methods like K-Means, FCM, and subtractive. To find which one is the best for our research, we have clustered the customers using K-Means, FCM, and subtractive clustering methods and compared the methods’ MSEs. The MSEs (Mean-Square Error) of the FCM is shown in Fig. 15. The error mean is = − 2.177e-0.6 and std. = 6.343e-0.5. The Mean squared error (MSE) measures the average of the squares of the errors