openapi: 3.1.0
info:
  title: XGBoost model API
  version: 1.0.0
components:
  schemas:
    data_model:
      type: object
      properties:
        scaler_method:
          type: string
          enum: ["MinMax", "Standard Scaler"]
          default: null
          example: "MinMax"
          description: "Scaling strategy."
        window_size:
          type: integer
          default: 0
          example: 3
          description: "Rolling window size used to generate lagged statistics for the target."
        use_filtering:
          type: boolean
          default: false
          example: false
          description: "Whether to filter rows based on a CI column during `fit` (expects a binary CI column)."
        transform_mode:
          type: string
          enum: ["all", "latest"]
          default: "all"
          example: "all"
          description: "Prediction mode, `'all'` to keep all rows or `'latest'` to return only the last row."
        arpr_config:
          type: object
          properties:
            ci_col:
              type: string
              x-feature: true
            ar_col:
              type: string
              x-feature: true
            pr_col:
              type: string
              x-feature: true
          example:
            ci_col: "col_1"
            ar_col: "col_2"
            pr_col: "col_3"
          description: "Optional configuration mapping for AR/PR substitution."
    opt_params:
      type: object
      properties:
        tree_method:
          type: string
          enum: ["hist", "exact", "approx"]
          default: "hist"
          example: "hist"
          description: "Tree construction algorithm."
        device:
          type: string
          enum: ["cuda", "cpu"]
          default: "cuda"
          example: "cuda"
          description: "Device for computation."
        learning_rate:
          type: number
          default: 0.3
          example: 0.3
          description: "Step size shrinkage to prevent overfitting."
        n_estimators:
          type: integer
          default: 100
          example: 100
          description: "Number of boosting rounds."
        max_depth:
          type: integer
          default: 32
          example: 32
          description: "Maximum depth of a tree."
        subsample:
          type: number
          minimum: 0.0
          maximum: 1.0
          default: 0.8
          example: 0.8
          description: "Subsample ratio of the training instances."
        colsample_bytree:
          type: number
          minimum: 0.0
          maximum: 1.0
          default: 0.8
          example: 0.8
          description: "Subsample ratio of columns when constructing each tree."
        min_child_weight:
          type: integer
          default: 5
          example: 5
          description: "Minimum sum of instance weight in a child node."
        random_state:
          type: integer
          default: 42
          example: 42
          description: "Seed for XGBoost random number generation."
        early_stopping_rounds:
          type: integer
          default: null
          example: 100
          description: "If set, enables early stopping."