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HomeGuidesAPI Reference
HomeGuidesAPI Reference🚀 Start now it's free 🚀Superwise Docs
HomeGuidesAPI Reference

👋 Introduction

  • Welcome aboard
  • Introduction to Superwise
  • Quickstart

💭 Let's talk concepts

  • Glossary overview
  • Models
  • Versions
  • Baselines
  • Segments
  • Metrics
    • Distribution metrics
    • Integrity metrics
    • Activity metrics
    • Drift calculations
    • Performance metrics
  • Policies
  • Incidents
  • Integrations
  • Transactions
  • Observability Levels

📔 How-to guides

  • Capabilities overview
  • Connecting
    • 1. Register a new model
    • 2. Upload a version
    • 3. Create a segment
    • 4. Log production predictions
    • 5. Log ground truth / Labels
    • End-to-end examples
    • Collecting data from S3
  • Integrations
    • Email
    • Webhook
    • PagerDuty
    • New Relic
    • Datadog
    • Slack
  • Account management
    • Manage your users
    • Generating tokens
    • Multi-Factor Authentication
    • SSO configuration
  • Monitoring
    • Drift
    • Data Quality
    • Activity
    • Model performance
    • Custom policies
  • Sagify Integration

💻 References

  • API and SDK Overview
  • REST API
    • API reference guide
  • Python SDK
    • PyPI package
    • Reference guide

☁️ Deployment

  • Deployment methods
  • Security center

🎓 Advanced

  • Consuming metrics via API
  • Retraining Notebook

💁🏻 Support

  • Help!
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Metrics

"Show me the metrics!"
-Jerry Maguire

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Superwise automatically discovers and computes an extensive set of metrics for each data entity in your dataset and gives you the ability to configure custom performance metrics. The available functions will vary according to the data type involved.

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Superwise metrics are divided into 4 types:

  • Distribution metrics
  • Integrity metrics
  • Activity metrics
  • Performance metrics

Updated 11 months ago