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models/xgboost/schemas.yaml

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+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."