{
  "id": "lib-process:data-science-ml--ab-testing-ml",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "ab-testing-ml",
    "description": "A/B Testing Framework for ML Models - Comprehensive framework for designing, executing, and analyzing\nA/B tests to compare ML model variants with statistical rigor, traffic management, and automated decision-making.",
    "libraryPath": "library/specializations/data-science-ml/ab-testing-ml.js",
    "specialization": "data-science-ml",
    "references": [
      "- Trustworthy Online Controlled Experiments: https://experimentguide.com/\n- Microsoft Experimentation Platform: https://exp-platform.com/\n- Optimizely Stats Engine: https://www.optimizely.com/insights/blog/stats-engine/\n- Netflix Experimentation: https://netflixtechblog.com/its-all-a-bout-testing-the-netflix-experimentation-platform-4e1ca458c15\n- Spotify Experimentation: https://engineering.atspotify.com/2020/10/spotifys-new-experimentation-platform-part-1/"
    ],
    "example": "const result = await orchestrate('specializations/data-science-ml/ab-testing-ml', {\n  projectName: 'Recommendation Engine A/B Test',\n  modelA: {\n    name: 'content-based-v1',\n    version: '1.2.0',\n    endpoint: 'https://api.example.com/models/content-based-v1'\n  },\n  modelB: {\n    name: 'collaborative-filtering-v2',\n    version: '2.0.0',\n    endpoint: 'https://api.example.com/models/collaborative-v2'\n  },\n  targetMetric: 'click_through_rate',\n  minimumSampleSize: 10000,\n  confidenceLevel: 0.95,\n  trafficSplit: { a: 50, b: 50 }\n});",
    "usesAgents": [
      "general-purpose"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:data-science-ml--ab-testing-ml",
      "to": "domain:data-science",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--ab-testing-ml",
      "to": "workflow:code-review",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--ab-testing-ml",
      "to": "workflow:ml-model-lifecycle",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:data-science-ml--ab-testing-ml",
      "to": "specialization:data-science-ml",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    }
  ],
  "incomingEdges": []
}