1. REST API for Oracle Machine Learning ServicesREST API for Oracle Machine Learning Services
  2. Work with Data Monitoring
  3. Data Monitoring Output Table Schema

Data Monitoring Output Table Schema

The Data Monitoring Output Table provides the schema for data monitoring output. The output data is written to a table specified by the user in the job request. This is a mandatory input. This table is created by Oracle Machine Learning Service and its format depends on the job type.

Output Data Format: The output data is written to the user specified output tables. This table is created by Oracle Machine Learning Services and its format also depends on the job type. The output schema name is outputSchemaName. You can overwrite the default by the outputSchemaName attribute.

Note:

Access to data sources is managed by database privileges.
The generated columns are prefixed with oml$ to distinguish them from supplemental column names which are copied as provided by the user.

Note:

The details are not generated unless topNDetails is set in the job request.

Table - Data Monitoring Output Table

Columns Types Description
START_TIME TIMESTAMP WITH TIME ZONE The start time of the monitoring.
EMD_TIME TIMESTAMP WITH TIME ZONE The end time of the monitoring.
IS_BASELINE NUMBER Indicates whether metrics are from baseline data. 1 indicates TRUE, and 0 indicates FALSE
THRESHOLD NUMBER The value used to decide the has_drift value.
HAS_DRIFT NUMBER Indicates whether a drift is detected. 1 indicates TRUE, and 0 indicates FALSE. Drift captures the relative change in performance between the baseline data and the new data period.
  • A drift above this threshold indicates a significant change in your data. Exceeding the threshold indicates that rebuilding and redeploying your model may be necessary.
  • A drift below this threshold indicates that there are insufficient changes in the data to warrant further investigation or action.
DRIFT NUMBER The magnitude of the drift
FEATURE_NAME VARCHAR2 The name of the predictor
FEATURE_TYPE VARCHAR2 "NUMERIC" or "CATEGORICAL"
IMPORTANCE_VALUE NUMBER The value indicates how impactful the column has been on data drift over a specified time period.
FEATURE_METRICS CLOB

Numeric:

{    
   "number_of_missing_values": number,
   "percentage_missing": number,
   "min_value": number,
   "max_value": number,
   "mean_value": number,
   "standard_deviation": number,
   "bin_distribution":
    [
        {
           "bin_upper_boundary": number,
           "bin_percentage": number
        },
        ......
    ],
   "anchor_feature": string,      
   "bi-variate_distribution":
    [
       {
          "bivariate_bin_upper_boundary": [number/string],
          "bin_percentage": number
       },
       ......
    ],   
   "population_stability_index"(only for new data): number,
   "jenson_shannon_distance"(only for new data): number,
   "bi-variate_psi"(only for new data): number,
   "bi-variate_jsd"(only for new data): number
 }

Categorical

{
  "number_of_missing_values": number,
  "percentage_missing": number,
  "number_of_unique_values": number,
  "topN_distribution":
   [
     {
        "value": string,
        "percentage": number
     },
     ......
   ],
  "anchor_feature": string,  
  "bi-variate_distribution":
   [
       {
          "bivariate_bin_upper_boundary": [number/string],
          "bin_percentage": number
       },
       ......
    ],
  "population_stability_index"(only for new data): number,
  "jenson_shannon_distance"(only for new data): number,
  "bi-variate_psi"(only for new data): number,
  "bi-variate_jsd"(only for new data): number
}
CREATION_TIME TIMESTAMP WITH TIME ZONE The time stamp when the results is created.