{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://schema.rtemis.org/hyperparameters/glmnet/v1/schema.json",
  "title": "rtemis GLMNETHyperparameters",
  "description": "Elastic net (glmnet). See `setup_GLMNET`.",
  "type": "object",
  "additionalProperties": false,
  "properties": {
    "alpha": {
      "oneOf": [
        {
          "type": "number",
          "minimum": 0,
          "maximum": 1
        },
        {
          "type": "array",
          "items": {
            "type": "number",
            "minimum": 0,
            "maximum": 1
          },
          "minItems": 1,
          "description": "Tuning search values."
        }
      ],
      "default": 1,
      "description": "Elastic net mixing parameter (0 = ridge, 1 = lasso)."
    },
    "family": {
      "type": ["string", "null"],
      "enum": ["gaussian", "binomial", "poisson", "multinomial", "cox", "mgaussian"],
      "default": null,
      "description": "GLM family. NULL = set from outcome type."
    },
    "offset": {
      "type": ["array", "null"],
      "items": {
        "type": "number"
      },
      "minItems": 1,
      "default": null,
      "description": "Offset. Must have one value per case."
    },
    "which_lambda_cv": {
      "type": "string",
      "enum": ["lambda.1se", "lambda.min"],
      "default": "lambda.1se",
      "description": "Which cross-validated lambda to use for prediction."
    },
    "nlambda": {
      "type": "integer",
      "minimum": 1,
      "default": 100,
      "description": "Number of lambda values."
    },
    "lambda": {
      "type": ["array", "null"],
      "items": {
        "type": "number",
        "minimum": 0
      },
      "minItems": 1,
      "default": null,
      "description": "Regularization strength. NULL = determined by cv.glmnet during tuning."
    },
    "penalty_factor": {
      "type": ["array", "null"],
      "items": {
        "type": "number",
        "minimum": 0
      },
      "minItems": 1,
      "default": null,
      "description": "Penalty factor, one per feature."
    },
    "standardize": {
      "type": "boolean",
      "default": true,
      "description": "Standardize features."
    },
    "intercept": {
      "type": "boolean",
      "default": true,
      "description": "Include intercept."
    },
    "ifw": {
      "oneOf": [
        {
          "type": "boolean"
        },
        {
          "type": "array",
          "items": {
            "type": "boolean"
          },
          "minItems": 1,
          "description": "Tuning search values."
        }
      ],
      "default": true,
      "description": "Inverse Frequency Weighting in classification."
    }
  }
}