You can use a data object as a source for probabilistic model data.
A probabilistic model performs optimally when you use the input data to the Labeler or Parser transformation as the source for the model reference data.
In Object Explorer, open or create a content set.
Select the
Content
view.
Select
Probabilistic Models
, and click
Add
.
The Probabilistic Model wizard opens.
Select the
Probabilistic Model from Data Objects
option.
Click
Next.
Enter a name for the probabilistic model.
Optionally, enter a text description of the model.
Browse the Model repository and select the data object that contains the data to import.
Do not select a social media data object.
Click
Next.
Review the columns on the data object, and select one or more columns to add to the model. You can add reference data columns and a label column in the same operation.
To import a column of data as reference data, select the column name and click
Data
.
You can select multiple data columns. The Developer tool merges the contents of the columns that you select to a single column.
To import a column of data as label values, select the column name and click
Label
.
When you import reference data and label values, the Developer tool assigns the label on each row to the reference data string on the same row. You can preview the data before you select the columns. You can change the label assignments after you create the model.
Click
Next.
Select the number of rows to import from the data source.
By default, the Developer tool imports all rows from the data source. If you enter a number, the model counts the rows from the start of the data set.
Specify the delimiters for the data values that you import.
You can specify different delimiters for reference data values and label values. The default delimiter is a character space.
Click
Finish
, and save the model.
After you create the probabilistic model, verify the label assignments and compile the model.