@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("DTClassifer")
@Description("A building stage for an Apache Spark ML Decision Tree classifier model. This stage expects "
+ "a dataset with at least two fields to train the model: One as an array of numeric values, and, "
+ "another that describes the class or label value as numeric value.")
public class DTClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("DTPredictor")
@Description("A prediction stage that leverages a trained Apache Spark ML Decision Tree classifier "
+ "or regressor model. The model type parameter determines whether this stage predicts from a classifier "
+ "or regressor model.")
public class DTPredictor extends PredictorCompute {

    ...

}

@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("GBTClassifer")
@Description("A building stage for an Apache Spark ML Gradient-Boosted Tree classifier model. This stage expects "
+ "a dataset with at least two fields to train the model: One as an array of numeric values, and, "  
+ "another that describes the class or label value as numeric value.")
public class GBTClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("GBTPredictor")
@Description("A prediction stage that leverages a trained Apache Spark based Gradient-Boosted Trees "
+ "classifier or regressor model. The model type parameter determines whether this stage predicts "
+ "from a classifier or regressor model.")

    ...

}

@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("LRClassifer")
@Description("A building stage for an Apache Spark ML Logistic Regression classifier model. This stage expects "
+ "a dataset with at least two fields to train the model: One as an array of numeric values, and, "  
+ "another that describes the class or label value as numeric value.")
public class LRClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("LRPredictor")
@Description("A prediction stage that leverages a trained Apache Spark ML Logistic "
+ "Regression classifier model.")
public class LRPredictor extends PredictorCompute {

    ...

}

@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("MLPClassifer")
@Description("A building stage for an Apache Spark ML Multi-Layer Perceptron classifier model. "
+ "This stage expects a dataset with at least two fields to train the model: One as an array of "
+ "numeric values, and, another that describes the class or label value as numeric value.")
public class MLPClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("MLPPredictor")
@Description("A prediction stage that leverages a trained Apache Spark ML Multi-Layer Perceptron "
+ "classifier model.")
public class MLPPredictor extends PredictorCompute {

    ...

}

@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("NBClassifer")
@Description("A building stage for an Apache Spark ML Naive Bayes classifier model. This stage expects "
+ "a dataset with at least two fields to train the model: One as an array of numeric values, and, "  
+ "another that describes the class or label value as numeric value.")
public class NBClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("NBPredictor")
@Description("A prediction stage that leverages a trained Apache Spark ML Naive Bayes classifier model.")
public class NBPredictor extends PredictorCompute {

    ...

}

@Plugin(type = SparkSink.PLUGIN_TYPE)
@Name("RFClassifer")
@Description("A building stage for an Apache Spark ML Random Forest Tree classifier model. This stage expects "
+ "a dataset with at least two fields to train the model: One as an array of numeric values, and, "  
+ "another that describes the class or label value as numeric value.")
public class RFClassifier extends ClassifierSink {

    ...

}

@Plugin(type = SparkCompute.PLUGIN_TYPE)
@Name("RFPredictor")
@Description("A prediction stage that leverages a trained Apache Spark ML Random Forest "
+ "classifier or regressor model. The model type parameter determines whether this stage "
+ "predicts from a classifier or regressor model.")		
public class RFPredictor extends PredictorCompute {

    ...

}