public abstract class PredictionModel<FeaturesType,M extends PredictionModel<FeaturesType,M>> extends Model<M>
| Constructor and Description |
|---|
PredictionModel() |
| Modifier and Type | Method and Description |
|---|---|
int |
numFeatures()
Returns the number of features the model was trained on.
|
M |
setFeaturesCol(String value) |
M |
setPredictionCol(String value) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms dataset by reading from
featuresCol, calling predict, and storing
the predictions as a new column predictionCol. |
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
|
transform, transform, transformequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoString, uidinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic M setFeaturesCol(String value)
public M setPredictionCol(String value)
public int numFeatures()
public StructType transformSchema(StructType schema)
PipelineStageCheck transform validity and derive the output schema from the input schema.
We check validity for interactions between parameters during transformSchema and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate().
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema in class PipelineStageschema - (undocumented)public Dataset<Row> transform(Dataset<?> dataset)
featuresCol, calling predict, and storing
the predictions as a new column predictionCol.
transform in class Transformerdataset - input datasetpredictionCol of type Doublepublic StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
schema - input schemafitting - whether this is in fittingfeaturesDataType - SQL DataType for FeaturesType.
E.g., VectorUDT for vector features.