Hospital Readmission Prediction — Random Forest Report
Random Forest predicting 30-day readmission for diabetic patients.
Training & Validation Metrics
| Metric | Value |
| N Samples Train | 626 |
| N Samples Val | 157 |
| N Features | 132 |
| N Estimators | 100 |
| Train Accuracy | 0.9904 |
| Val Accuracy | 0.8854 |
| Train Auc | 1.0000 |
| Val Auc | 0.4639 |
| Val Precision | 0.0000 |
| Val Recall | 0.0000 |
| Val F1 | 0.0000 |
Confusion Matrix (Validation Set)
|
Predicted: Not Readmitted |
Predicted: Readmitted (<30d) |
| Actual: Not Readmitted |
TN = 139 |
FP = 1 |
| Actual: Readmitted (<30d) |
FN = 17 |
TP = 0 |
Classification Report
precision recall f1-score support
Not Readmitted 0.89 0.99 0.94 140
Readmitted <30d 0.00 0.00 0.00 17
accuracy 0.89 157
macro avg 0.45 0.50 0.47 157
weighted avg 0.79 0.89 0.84 157
Training History
ROC Curve (Validation Set)
Feature Importance — Top 20 (Gini Importance)