Predictive Modeling Validation Metrics
The Predictive Modeling Validation Metrics Dataset is used to power the Validation Metrics section of the Pipeline with Predictive Modeling Dashboard. The dataset contains metrics produced while validating the quality of the trained model.
The dataset is refreshed at the same cadence as the Predictive Model is refreshed - monthly by default. Only the most recently produced results are displayed in the dashboard.
|
Field Name |
Field Type |
Description |
|
Report Date |
DATE |
The date being used to compare predicted vs. actual. |
|
Predicted Values |
DOUBLE PRECISION |
The predicted conversions from the model for this report date. |
| Actual Values | DOUBLE PRECISION | The actual number of conversions that occurred on this report date. |
| Lower Prediction | DOUBLE PRECISION | Lower bound of the 90% HPDI region for predicting the target. A conservative estimate of the smallest value the target will take in real life. |
| Upper Predictions | DOUBLE PRECISION | Upper bound of the 90% HPDI region for predicting the target. A conservative estimate of the largest value the target will take in real life. |
| Spend | DOUBLE PRECISION | The amount spent on this feature. |
| Control | DOUBLE PRECISION | |
| Feature | TEXT | Name of the feature in the model. I.e. Paid Social, Display, etc. |
| Pred Actual | DOUBLE PRECISION | The difference between the predicted values and actual values. |
| R Squared | DOUBLE PRECISION | The R-squared metric for the model (deprecated) |
| Mean Squared Error | DOUBLE PRECISION | The Mean-Squared Error for the model. |
| SMAPE | DOUBLE PRECISION | The sMAPE metric for the model. |
| Intercept | DOUBLE PRECISION | 1 - R2 |
| Model ID | TEXT | ID to identify the trained model used for optimization. |
| Target Variable Pretty | TEXT |
A more descriptive name for the target variable to be displayed in the dashboard.
|
| Target Variable | TEXT | The name of the field the model is trained to predict. |
| OneView Name | TEXT | The name of the OneView data is pulled from to model. |
| Feature Type | TEXT | The name of the feature used to predict the target variable. |
| Conversion Name | TEXT | The name of the field the model is trained to predict. |
| Category | TEXT | Name of the category in the model. I.e. Client 1, Client 2, Line of Business 1, Line of Business 2, etc. |
| Category Type | TEXT | The name of the category used to create a hierarchy |
| Is Active | BOOLEAN | |
| Model Run Date | DATE | Date the model was trained. |
| Training Start Date | TIMESTAMP | Earliest date provided to the model in training. |
| Training End Date | TIMESTAMP | Most recent date provided to the model in training. |
| Most Recent Model | INTEGER | |
| Min Daily Cost | DOUBLE PRECISION | Smallest amount spent in a single day summed across all channels. |
| Max Daily Cost | DOUBLE PRECISION | Largest amount spent in a single day summed across all channels. |
| Insert Date | TIMESTAMP | The date in which the record was loaded into the data warehouse |
| Channelmix Profile | TEXT | The ChannelMix Profile associated to the data |
Version 2022.4