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Scoring Model.md
TradeGuard Shield starts with an explainable rule-based model. Machine learning can be added later once labeled datasets and review workflows exist.
flowchart LR
A["0-30 High Risk"] --> Red[Red Badge]
B["31-60 Medium Risk"] --> Yellow[Yellow Badge]
C["61-100 Low Risk"] --> Green[Green Badge]
pie title Current Risk Penalty Categories
"Threat-feed match" : 55
"Very young domain" : 30
"No regulator match" : 20
"Invalid TLS" : 18
"Suspicious claims" : 20
"Negative reviews" : 12
"Social spike" : 10
"WHOIS privacy" : 8
Every scoring reason must include:
codeseveritydetailsource- optional
evidenceUrl
flowchart TD
Rules[Transparent Rules] --> Dataset[Labeled Dataset]
Dataset --> Calibration[Threshold Calibration]
Calibration --> ML[Optional ML Classifier]
ML --> Audit[Independent Methodology Audit]
This repository is an open-source project and encourages contributions. Please see the CONTRIBUTING.md file for guidelines on how to report issues or submit pull requests.
This project is licensed under the terms of the MIT License. See the LICENSE file for full details.
Copyright (c) 2024 Ciprian-LocalPulse
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