Step 4 (Model building)

I used the RF and KNN models for my analysis. including all 23 features found important by RF resulted in :

-----RF Model Prediction------ confustion matrix is : [[599 592] [687 689]] calssification report is : precision recall f1-score support

       `0       0.47      0.50      0.48      1191`
       `1       0.54      0.50      0.52      1376`

`accuracy                           0.50      2567`

macro avg 0.50 0.50 0.50 2567 weighted avg 0.50 0.50 0.50 2567

Accuracy score is: 0.5017530190884301 -----KNN Model Prediction------ confustion matrix is : [[599 592] [687 689]] calssification report is : precision recall f1-score support

       `0       0.47      0.50      0.48      1191`
       `1       0.54      0.50      0.52      1376`

`accuracy                           0.50      2567`

macro avg 0.50 0.50 0.50 2567 weighted avg 0.50 0.50 0.50 2567

Accuracy score is: 0.5017530190884301