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object Predictors

Object for instantiating a Model which extends the org.apache.spark.ml.PredictionModel

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  9. def getPredictor(): Model
  10. def getPredictor(options: TimeSeriesOptions): Model

    Retrieves a single DataRobot model, if it is the only one in the specified classloader

    Retrieves a single DataRobot model, if it is the only one in the specified classloader

    returns

    Spark compatible Scoring Code model

  11. def getPredictor(modelId: String): Model
  12. def getPredictor(modelId: String, options: TimeSeriesOptions): Model

    Retrieves a DataRobot model by a modelId

    Retrieves a DataRobot model by a modelId

    modelId

    unique model id for the Scoring Code model. The model should be in a classpath

    returns

    Spark compatible Scoring Code model

  13. def getPredictor(filePath: String, modelId: String): Model
  14. def getPredictor(filePath: String, modelId: String, options: TimeSeriesOptions): Model

    Retrieves a DataRobot model from a Scoring Code model jar file on a local file system

    Retrieves a DataRobot model from a Scoring Code model jar file on a local file system

    filePath

    an absolute or relative path to a local file. Example: ../testcases/iris/5e96ed57a6714a18ad699582.jar

    modelId

    unique model id for the Scoring Code model

    returns

    Spark compatible Scoring Code model

  15. def getPredictor(modelBytes: Array[Byte], modelId: String): Model
  16. def getPredictor(modelBytes: Array[Byte], modelId: String, options: TimeSeriesOptions): Model

    Retrieves a DataRobot model from a byte array out of a Scoring Code model jar file

    Retrieves a DataRobot model from a byte array out of a Scoring Code model jar file

    modelBytes

    byte array from a Scoring Code model file

    modelId

    unique model id for the Scoring Code model

    returns

    Spark compatible Scoring Code model

  17. def getPredictorFromDeployment(host: String, deploymentId: String, token: String): Model
  18. def getPredictorFromDeployment(host: String, deploymentId: String, token: String, options: TimeSeriesOptions): Model

    Downloads a model from a DataRobot deployment and creates a Spark compatible Scoring Code model

    Downloads a model from a DataRobot deployment and creates a Spark compatible Scoring Code model

    host

    DataRobot host. e.g "https://app.datarobot.com"

    deploymentId

    id of a deployment with a Scoring Code model. e.g "612e5ade15947d9034ea68c6"

    token

    user access token in a DataRobot instance. e.g "wu74mU2FvdvdZV8gNbTanc-PDrK4El3H"

    returns

    Spark compatible Scoring Code model

  19. def getPredictorFromDeployment(host: String, deploymentId: String, modelId: String, token: String): Model
  20. def getPredictorFromDeployment(host: String, deploymentId: String, modelId: String, token: String, options: TimeSeriesOptions): Model

    Downloads a model from a DataRobot deployment and creates a Spark compatible Scoring Code model

    Downloads a model from a DataRobot deployment and creates a Spark compatible Scoring Code model

    host

    DataRobot host. e.g "https://app.datarobot.com"

    deploymentId

    id of a deployment with a Scoring Code model. e.g "612e5ade15947d9034ea68c6"

    modelId

    unique modelId. e.g "5d67c1f938934701a8c3c9f1"

    token

    user access token in a DataRobot instance. e.g "wu74mU2FvdvdZV8gNbTanc-PDrK4El3H"

    returns

    Spark compatible Scoring Code model

  21. def getPredictorFromHdfs(hdfsPath: String, spark: SparkSession, modelId: String, options: TimeSeriesOptions = null): Model

    Retrieves a DataRobot model from a Scoring Code model jar file on an HDFS file system

    Retrieves a DataRobot model from a Scoring Code model jar file on an HDFS file system

    hdfsPath

    absolute or relative path to a model jar on HDFS

    spark

    SparkSession instance to acquire HDFS configuration from

    modelId

    unique model id for the Scoring Code model

    returns

    Spark compatible Scoring Code model

  22. def getPredictorFromServer(url: String, token: String): Model
  23. def getPredictorFromServer(url: String, token: String, options: TimeSeriesOptions): Model

    Downloads a model from a DataRobot instance and creates a Spark compatible Scoring Code model

    Downloads a model from a DataRobot instance and creates a Spark compatible Scoring Code model

    url

    ScoringCode model URL. e.g "https://app.datarobot.com/projects/5e96ecf8617f2318c8a18149/models/5e96ed57a6714a18ad699582/blueprint"

    token

    user access token in a DataRobot instance. e.g "wu74mU2FvdvdZV8gNbTanc-PDrK4El3H"

    returns

    Spark compatible Scoring Code model

  24. def getPredictorFromServer(host: String, projectId: String, modelId: String, token: String): Model
  25. def getPredictorFromServer(host: String, projectId: String, modelId: String, token: String, options: TimeSeriesOptions): Model

    Downloads a model from a DataRobot instance and creates a Spark compatible Scoring Code model

    Downloads a model from a DataRobot instance and creates a Spark compatible Scoring Code model

    host

    DataRobot host. e.g "https://staging.datarobot.com"

    projectId

    DataRobot projectId. e.g "5d67c1a53893470196c3ca7e"

    modelId

    unique modelId. e.g "5d67c1f938934701a8c3c9f1"

    token

    user access token in a DataRobot instance. e.g "wu74mU2FvdvdZV8gNbTanc-PDrK4El3H"

    returns

    Spark compatible Scoring Code model

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