Model Performance Dashboard

Binary Classification Model Evaluation Metrics

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ROC AUC

98.32%

PR AUC

95.61%

Accuracy

94.62%

Macro F1

93.39%

Confusion Matrix

Model prediction distribution across classes

True Negative

1317

68.8%

False Positive

47

2.5%

False Negative

56

2.9%

True Positive

493

25.8%

Predicted Negative

1373

Predicted Positive

540

Classification Report

Per-class performance metrics

Class
Precision
Recall
F1-Score
Support
NOT CONFIRMED
95.9%
96.6%
96.2%
1364
CONFIRMED
91.3%
89.8%
90.5%
549
Macro Avg
93.6%
93.2%
93.4%
1913
Weighted Avg
94.6%
94.6%
94.6%
1913

Dataset & Model Information

Training data and model configuration details

Total Rows

9,564

Labeled Rows

9,564

Numeric Features

13

Categorical Features

0

Best Threshold

0.4433

Class Balance

1364 / 549