Creating a Probabilistic Model from a Data Object
You can use a data object as a source for probabilistic model data. For example, use the source data object from the mapping that reads the probabilistic model. You can also profile an object in the mapping and create a data object from the profile results.
A probabilistic model performs optimally when you use the input data from the Labeler or Parser transformation as the source for the model reference data. For example, you can run a profile on the transformation object in the mapping. Create a data object from the profile results.
1. Open or create a content set.
2. Select the Content view.
3. Select Probabilistic Models, and click Add.
The Probabilistic Model wizard opens.
4. Select the Probabilistic Model from Data Objectsoption.
Click Next.
5. Enter a name for the probabilistic model.
Optionally, enter a text description of the model.
6. Browse the Model repository and select the data object that contains the reference data.
Click Next.
7. Review the data columns on the data object, and select the columns to add to the probabilistic model.
- - To add a data column as reference data, select the column name and click Data. You can add more than one column of reference data. The import operation joins the columns so that the values from the same row in each column appear on the same data row in the model.
- - To use a data column as a source for label values, select the column name and click Label. You can add more than one column of label data. The import operation concatenates the columns so that the values from each column appear beneath each other in a single column in the model.
Click Next.
8. Select the number of rows to copy from the data source.
Select all rows, or specify the number of rows to copy. If you enter a number, the model counts the rows from the start of the data set.
9. Set the delimiters to use for the reference data values. Specify a delimiter to identify multiple values that represent a single piece of information.
The default delimiter is a character space.
10. Click Finish and save the model.
The probabilistic model opens in the Developer tool.
After you create the probabilistic model, assign the labels to the data values and compile the model.