27.3.9.1 AnomalyDetector Class

This class encapsulates the anomaly detection task as described in Anomaly Detection. AnomalyDetector supports methods for loading, training, and unloading models, predicting labels, calculating probabilities, and related tasks.

AnomalyDetector provides the following accessible properties:

name (String): The model name.
metadata (Object): Model metadata in the model catalog. See Model Metadata.
trainOptions (Object): The training options specified in the constructor when creating an instance of AnomalyDetector.

AnomalyDetector Constructor

The AnomalyDetector class constructor is shown here:

AnomalyDetector class constructor

new ml.AnomalyDetector(
  String name[, 
  Object trainOptions]
)

Arguments

name (String): Unique identifier for this AnomalyDetector.
trainOptions (Object) (optional): Training options; the same as the training options which can be used with sys.ML_TRAIN.

Return type

An instance of AnomalyDetector.

AnomalyDetector.train()

Trains and loads a new anomaly detector. This method acts as a wrapper for both sys.ML_TRAIN and sys.ML_MODEL_LOAD, but is specific to HeatWave AutoML anomaly detection.

Signature

AnomalyDetector.train(
  Table trainData, 
  String targetColumnName
)

Arguments

trainData (Table): A Table containing a training dataset. The table must not take up more than 10 GB space, or hold more than 100 million rows or more than 1017 columns.
targetColumnName (String): Name of the target column containing ground truth values. The type used for this column cannot be TEXT.

Return type

None.

AnomalyDetector.fit()

An alias for train(), and identical to it in all respects other than name. See AnomalyDetector.train(), for more information.

AnomalyDetector.predict()

This method predicts labels, acting as a wrapper for sys.ML_PREDICT_ROW.

Predicts a label for a single sample of data, and returns the label. See ML_PREDICT_ROW, for more information.

Signature

String AnomalyDetector.predict(
  Object sample[,
  Object options]
)

Arguments

sample (Object): Sample data. This argument must contain members that were used for training; extra members may be included, but these are ignored during prediction.
options (Object) (optional): Set of one of more options.

Return type

String.

AnomalyDetector.score()

This method serves as a JavaScript wrapper for sys.ML_SCORE, returning the score for the test data in the specified table and column. For possible metrics, see Optimization and Scoring Metrics.

Signature

score(
  Table testData,
  String targetColumnName, 
  String metric[, 
  Object options]
)

Arguments

testData (Table): Table containing test data to be scored; must contain the same columns as the training dataset.
targetColumnName (String): Name of the target column containing ground truth values.
metric (String): Name of the scoring metric to use. See Optimization and Scoring Metrics, for information about metrics which can be used for AutoML anomaly detection.
options (Object) (optional): A set of options in JSON object format. See the description of ML_SCORE for more information.

Return type

Number.

AnomalyDetector.unload()

This method is a wrapper for sys.ML_MODEL_UNLOAD, and Unloads the model.

Signature

```
AnomalyDetector.unload()
```

Arguments

None.

Return type

None.