Table 7 Performance parameters, precision, and sensitivity of the decision tree models
From: The use of knowledge extraction in predicting customer churn in B2B
Performance parameter | Logistic regression E9 | Logistic regression E10 | Logistic regression M9 | Logistic regression M10 |
|---|---|---|---|---|
Kappa | 0.257 | − 0.500 | − 0.705 | 0.148 |
Threshold | − 0.198 | 0.751 | 1.183 | − 1.293 |
Precision | − 0.938 | − 0.226 | 0.142 | − 2.526 |
Sensitivity | 0.429 | 0.190 | − 0.285 | 0.809 |
Performance parameter | Neural Network E9 | Neural Network E10 | Neural Network M9 | Neural Network M10 |
|---|---|---|---|---|
Kappa | 0.157 | 0.600 | 0.805 | 0.048 |
Threshold | 0.298 | 0.651 | 1.083 | 1.393 |
Precision | 1.038 | 0.326 | 0.042 | 2.626 |
Sensitivity | 0.329 | 0.090 | 0.385 | 0.709 |