PREDICT_XGB_CLASSIFIER

Applies an XGBoost classifier model on an input relation.

Applies an XGBoost classifier model on an input relation. PREDICT_XGB_CLASSIFIER returns a VARCHAR data type that specifies one of the following, as determined by how the type parameter is set:

  • The predicted class (based on probability scores)

  • Probability of a class for each input instance.

Syntax

PREDICT_XGB_CLASSIFIER ( input-columns
          USING PARAMETERS model_name = 'model-name'
              [, type = 'prediction-type' ]
              [, class = 'user-input-class' ]
              [, match_by_pos = 'match-by-position' ]
              [, probability_normalization = 'prob-normalization' ] )

Arguments

input-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).

type
Type of prediction to return, one of the following:

  • response (default): The class with the highest probability among all possible classes.

  • probability: Valid only if the class parameter is set, returns for each input instance the probability of the specified class or predicted class.

class
Class to use when the type parameter is set to probability. If you omit this parameter, the function uses the predicted class—the one with the highest probability score. Thus, the predict function returns the probability that the input instance belongs to the specified or predicted class.
match_by_pos

Boolean value that specifies how input columns are matched to model features:

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

  • false (default): Match by name.

probability_normalization

The classifier's normalization method, either softmax (multi-class classifier) or logit (binary classifier). If unspecified, the default logit function is used for normalization.

Examples

Use PREDICT_XGB_CLASSIFIER to apply the classifier to the test data:

=> SELECT PREDICT_XGB_CLASSIFIER (Sepal_Length, Sepal_Width, Petal_Length, Petal_Width
    USING PARAMETERS model_name='xgb_iris', probability_normalization='logit') FROM iris1;
PREDICT_XGB_CLASSIFIER
------------------------
setosa
setosa
setosa
.
.
.
versicolor
versicolor
versicolor
.
.
.
virginica
virginica
virginica
.
.
.

(90 rows)

See XGBoost for classification for more examples.