Predict a label for each event in the table using a model that was trained using the createModelFromNumericValues operator.

For example, consider a table with these columns: longitude, latitude, and city name. Train a model to predict a city name from given longitude and latitude (actual or closest city), such as the following:

29°45′46", 95°22′59″ => Houston, TX, USA

Operator Usage in Easy Mode

Click + on the parent node.
Enter the Predict Label from Numeric Values operator in the search field and select the operator from the Results to open the operator form.
In the Table drop-down, enter or select the name of the table to apply the prediction.
In the Model Name drop-down, enter or select the name of the model.
Optional. In the Column Names, click Add More to add the list of column names used to predict the label.
Click Run to view the result.
Click Save to add the operator to the playbook.
Click Cancel to discard the operator form.

Usage Details

LQL Command

predictLableFromNumericValues(table, outputModelName, listOfColumns)

Input
table: Input table to train a model.
outputModelName: Model name to store the trained model. Trained models are not displayed in the UI, so remember the name of the model that was created. If a model with the same name exists, this operation overwrites it without notification.
listOfColumns: List of columns to train a model to learn label such as "col1", "col2", "col3".

Output:

Input table + lhub_predicted_label and lhub_confidence_score.

Example

This example predicts gender from height and weight inputs.

Input
table

id	height	weight
1	70	190
2	63	120

LQL command

predictLabelFromNumericValues(table,"genderFromHeightWeight", "height", "weight")

Output

id	height	weight	lhub_predicted_label
1	70	190	male
2	63	120	female

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