Machine Learning Model
Performance metrics and features evaluation of the supervised learning model
Accuracy
82.00%
On validation set
Precision
80.00%
True positives / Predicted positives
Recall
72.00%
True positives / Actual positives
F1 Score
90.00%
Harmonic mean of precision & recall
Features Evaluation
Feature importance scores sorted by evaluation
Model Information
Configuration and training details
82%
Overall Accuracy
Used Algorithm
svm algorithm
Training Data Size
22078 records
Training Datetime
2025-12-30 22:05
Learning Type
Supervised Classification
Transaction Records
Machine Learning Fraud Score predictions for all transactions
| Date & Time | Type | Amount | ML Risk Score |
|---|