openapi: 3.1.0
info:
  title: Linear Regression model API
  version: 1.0.0
components:
  schemas:
    model:
      type: object
      properties:
        degree:
          type: integer
          default: 1
          example: 2
          description: "Degree of the polynomial used to create polynomial features."
        interaction_only:
          type: boolean
          default: false
          example: true
          description: "Whether to include only interaction features in polynomial features."
        verbose:
          type: boolean
          default: false
          example: true
          description: "Enable verbose output during model execution."
        clipping_max:
          type: integer
          default: null
          example: 100
          description: "Maximum value for clipping prediction output."
        clipping_min:
          type: integer
          default: null
          example: 0
          description: "Minimum value for clipping prediction output."
    data_model:
      type: object
      properties:
        verbose:
          type: boolean
          default: false
          example: true
          description: "Enable verbose output during model execution."
        StepsList: &steps_list
          - "Discontinuity Treatment"
          - "Lag Selection"
          - "Range Selection & Data Removal"
          - "Static Window Removal"
          - "Define Variables Limits"
          - "Normalization"
          - "Feature Creation"
          - "Lag Creation"
        steps_order:
          type: array
          items:
            type: string
            enum: *steps_list
          required: *steps_list
          default: *steps_list
          example: *steps_list
          uniqueItems: true
          description: "Order of the steps to be executed in the pipeline."
        nan_treatment:
          type: string
          enum: ["drop", "linear interpolation"]
          default: "drop"
          example: "drop"
          description: "The treatment for missing values."
        lag_train:
          type: object
          x-feature: true
          additionalProperties:
            type: integer
          example: { "col_2": 1 }
          default: {}
          description: "The lags for each variable to be applyed during training. Format: {'variable_name': lag}"
        lag_transform:
          type: object
          x-feature: true
          additionalProperties:
            type: integer
          example: { "col_2": 1 }
          default: {}
          description: "The lags for each variable to be applyed during transformation. Format: {'variable_name': lag}"
        start_date:
          type: string
          format: "date-time"
          default: null
          example: "2020-01-01 00:00:00"
          description: "The start date for the dataset. Format: 'YYYY-MM-DD HH:MM:SS'"
        end_date:
          type: string
          format: "date-time"
          default: null
          example: "2020-04-25 00:00:00"
          description: "The end date for the dataset. Format: 'YYYY-MM-DD HH:MM:SS'"
        removed_intervals:
          type: array
          items:
            type: array
            items:
              type: string
              format: "date-time"
          example:
            - ["2020-01-01 00:00:00", "2020-01-02 00:00:00"]
          default: []
          description: "The intervals to be removed from the dataset. Format: [[start_date, end_date], ...]"
        static_threshold:
          type: integer
          default: null
          example: 10
          description: "The number of repeated values to be considered as static"
        lower_limits:
          type: object
          x-feature: true
          additionalProperties:
            type: number
          example:
            { "col_2": 0 }
          default: {}
          description: "The lower limits for each variable. Format: {'variable_name': limit}"
        upper_limits:
          type: object
          x-feature: true
          additionalProperties:
            type: number
          example:
            { "col_2": 100 }
          default: {}
          description: "The upper limits for each variable. Format: {'variable_name': limit}"
        scaler_name:
          type: string
          enum:
            - "Standard Scaler"
          default: "Standard Scaler"
          example: "Standard Scaler"
          description: "The scaler name."
        scaler_params:
          type: object
          additionalProperties:
            type: object
            properties:
              mean:
                type: number
              variance:
                type: number
            required:
              - mean
              - variance
          example:
            { "col_2": { "mean": 0, "variance": 1 }}
          default: {}
          description: "The parameters for the scaler object."
        self_operations:
          type: array
          items:
            type: object
            properties:
              variable:
                type: string
                x-feature: true
              operation:
                type: string
                enum: ["exp", "pow", "log", "root"]
              scalar:
                type: number
            required:
              - variable
              - operation
              - scalar
          example: [{ "variable": "col_2", "operation": "pow", "scalar": 2 }]
          default: []
          description: "The operations for feature creation using the same variable."
        cross_operations:
          type: array
          items:
            type: object
            properties:
              variable1:
                type: string
                x-feature: true
              variable2:
                type: string
                x-feature: true
              operation:
                type: string
                enum: ["*", "/"]
            required:
              - variable1
              - variable2
              - operation
          example:
            [{ "variable1": "col_2", "variable2": "col_3", "operation": "*" }]
          default: []
          description: "The operations for feature creation using two variables."
        created_lags:
          type: object
          x-feature: true
          additionalProperties:
            type: array
            items:
              type: integer
          example:
            { "col_2": [1, 2] }
          default: {}
          description: "Variables created by lagging existing ones."