Kristian Larsen
3 jan 2019
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The below output shows The loan amount with regards to number of loans
The below plot shows a box plot of the loan amount with respect to different loan status
loan status | |||
---|---|---|---|
Predictors | Odds Ratios | CI | p |
(Intercept) | 0.05 | 0.05 – 0.05 | <0.001 |
loan amnt | 1.00 | 1.00 – 1.00 | <0.001 |
home_ownership1 | 0.85 | 0.83 – 0.87 | <0.001 |
verification status | 1.12 | 1.09 – 1.15 | <0.001 |
purpose 0 | 0.71 | 0.67 – 0.76 | <0.001 |
purpose 1 | 0.67 | 0.63 – 0.72 | <0.001 |
dti1 | 0.81 | 0.79 – 0.83 | <0.001 |
delinq_2yrs1 | 0.95 | 0.92 – 0.98 | 0.001 |
int rate | 121500.43 | 89535.70 – 164876.74 | <0.001 |
inq last 6 mths | 1.02 | 1.01 – 1.03 | <0.001 |
mths since last delinq | 1.00 | 1.00 – 1.00 | <0.001 |
revol bal | 1.00 | 1.00 – 1.00 | <0.001 |
revol util | 1.43 | 1.36 – 1.51 | <0.001 |
total acc | 1.00 | 0.99 – 1.00 | <0.001 |
Observations | 214008 | ||
Cox & Snell’s R2 / Nagelkerke’s R2 | 0.049 / 0.083 |
The below table is a ROC curve of the logistic regression credit model. The value displays how well the model have explained the outcome.
## [[1]]
## [1] 0.6695527