PREDICT_RF_CLASSIFIER_CLASSES

Applies a random forest model on an input relation and returns the probabilities of classes:.

Applies a random forest model on an input relation and returns the probabilities of classes:

  • VARCHAR predicted column contains the class label with the highest vote (popular vote).

  • Multiple FLOAT columns, where the first probability column contains the probability for the class reported in the predicted column. Other columns contain the probability of each class specified in the classes parameter.

  • Key columns with the same value and data type as matching input columns specified in parameter key_columns.

Syntax

PREDICT_RF_CLASSIFIER_CLASSES ( predictor-columns
        USING PARAMETERS model_name = 'model-name'
            [, key_columns = 'key-columns']
            [, exclude_columns = 'excluded-columns']
            [, classes = 'classes']
            [, match_by_pos = match-by-position] )
OVER( [window-partition-clause] )

Arguments

predictor-columns
Comma-separated list of columns to use from the input relation, or asterisk (*) to select all columns.

Parameters

model_name

Name of the model (case-insensitive).

key_columns

Comma-separated list of predictor column names that identify the output rows. To exclude these and other predictor columns from being used for prediction, include them in the argument list for parameter exclude_columns.

exclude_columns
Comma-separated list of columns from predictor-columns to exclude from processing.
classes
Comma-separated list of class labels in the model. The probability of belonging to this given class is predicted by the classifier. Values are case sensitive.
match_by_pos
Boolean value that specifies how predictor columns are matched to model features:

  • false (default): Match by name.

  • true: Match by the position of columns in the predictor columns list.

Examples

=> SELECT PREDICT_RF_CLASSIFIER_CLASSES(Sepal_Length, Sepal_Width, Petal_Length, Petal_Width
                               USING PARAMETERS model_name='myRFModel') OVER () FROM iris;
predicted  |    probability
-----------+-------------------
setosa     |                 1
setosa     |              0.99
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |              0.97
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |              0.99
...
(150 rows)

This example shows how to use function PREDICT_RF_CLASSIFIER_CLASSES, using the match_by_pos parameter:

=> SELECT PREDICT_RF_CLASSIFIER_CLASSES(Sepal_Length, Sepal_Width, Petal_Length, Petal_Width
                          USING PARAMETERS model_name='myRFModel', match_by_pos='true') OVER () FROM iris;
predicted  |    probability
-----------+-------------------
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
setosa     |                 1
...
(150 rows)s

See also