PostHog · Schema

OCSVMDetectorConfig

A/B TestingAnalyticsFeature FlagsOpen SourceProduct AnalyticsSession Recording

Properties

Name	Type	Description
kernel	string	SVM kernel type (default: "rbf")
nu	number	Upper bound on training errors fraction (default: 0.1)
preprocessing	object	Preprocessing transforms applied before detection
threshold	number	Anomaly probability threshold (default: 0.9)
type	string
window	integer	Rolling window size — how many historical data points to train on (default: based on calculation interval)

View JSON Schema on GitHub

JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/OCSVMDetectorConfig",
  "title": "OCSVMDetectorConfig",
  "additionalProperties": false,
  "properties": {
    "kernel": {
      "default": null,
      "description": "SVM kernel type (default: \"rbf\")",
      "title": "Kernel",
      "type": "string",
      "nullable": true
    },
    "nu": {
      "default": null,
      "description": "Upper bound on training errors fraction (default: 0.1)",
      "title": "Nu",
      "type": "number",
      "nullable": true
    },
    "preprocessing": {
      "default": null,
      "description": "Preprocessing transforms applied before detection",
      "allOf": [
        {
          "$ref": "#/components/schemas/PreprocessingConfig"
        }
      ],
      "nullable": true
    },
    "threshold": {
      "default": null,
      "description": "Anomaly probability threshold (default: 0.9)",
      "title": "Threshold",
      "type": "number",
      "nullable": true
    },
    "type": {
      "default": "ocsvm",
      "title": "Type",
      "type": "string",
      "enum": [
        "ocsvm"
      ]
    },
    "window": {
      "default": null,
      "description": "Rolling window size \u2014 how many historical data points to train on (default: based on calculation interval)",
      "title": "Window",
      "type": "integer",
      "nullable": true
    }
  },
  "type": "object"
}