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Snowflake H2O MOJO Predictor (Isolation Forest)

AnalyticsIntegrationsH2O Machine LearningMOJOsSnowflake
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This node applies an Isolation Forest MOJO to an incoming Snowflake connection in order to detectanomalies/outliers. The output of the node will consist of the input and, depending on the settings, one or two appended columns. One is the prediction which contains normalized anomaly score. The higher the score, the more likely it is an anomaly. The other (optionally) appended column contains the mean length of the predicted decision tree paths of each observation. The shorter, the more likely it is an anomaly.

Node details

Input ports
  1. Type: MOJO
    MOJO (AnomalyDetection)
    The MOJO. Its model category must be anomaly detection.
  2. Type: DB Data
    DB Data
    The DB Data object that should be used for prediction
Output ports
  1. Type: DB Data
    Predicted DB Data
    The DB Data object containing the predicted (normalized) anomaly score and, if selected, the mean length.

Extension

The Snowflake H2O MOJO Predictor (Isolation Forest) node is part of this extension:

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Related workflows & nodes

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