Report, Chart and Dashboard Deployment

The this article discusses the details in training/test datasets and related meta data, sample/scoring datasets and related meta data, and model meta data in deployment.

    Example (a few record from the purchase dataset): The target variable is Purchased.

    User ID Gender Age EstimatedSalary Purchased
    15624510 Male 19 19000 0
    15810944 Male 35 20000 0
    15668575 Female 26 43000 0
    15603246 Female 27 57000 0
    15804002 Male 19 76000 0
    15728773 Male 27 58000 0

    It is important that fields in the model meta data must match the variables passed to the Python function adapter in order for model consumption to work

    Setting 1

    1. Fields in the training/test data sets (no need for meta data): User ID, Gender, Age, EstimatedSalary, Purchased
      1. The training/test datasets are used in the training script/notebook and may have all the variables/fields
    2. Fields in the sample data set and related meta data: User ID, Gender, Age, EstimatedSalary
      1.  No target variable, but may contain the rest
    3. Fields in the scoring data set and related meta data: User ID, Gender, Age, EstimatedSalary
      1. No target variable, but may contain the rest
    4. Fields in the model meta data: Age, EstimatedSalary, Purchased
      1. Only contains fields/variables in the model
      2. May need to manually remove unnecessary fields from the generated meta data
    5. Fields passed to the Python function adapter in the report: Age, EstimatedSalary, Purchased
      1. Note: Only contains fields/variables in the model

    Setting 2

    1. Fields in the training/test data sets (no need for meta data): User ID, Gender, Age, EstimatedSalary, Purchased
      1. Note: The training/test datasets are used in the training script/notebook and may have all the variables/fields
    2. Fields in the sample data set and related meta data: Age, EstimatedSalary
      1. Note: No target variable, and contains only variables in the model
    3. Fields in the scoring data set and related meta data: Age, EstimatedSalary
      1. Note: No target variable, and contains only variables in the model
    4. Fields in the model meta data: Age, EstimatedSalary, Purchased
      1. Note: Only contains fields/variables in the model
    5. Fields passed to the Python function adapter in the report: Age, EstimatedSalary, Purchased
      1. Note: Only contains fields/variables in the model