public class ImputerModel extends Model<ImputerModel> implements ImputerParams, MLWritable
Imputer.
param: surrogateDF a DataFrame containing inputCols and their corresponding surrogates, which are used to replace the missing values in the input DataFrame.
| Modifier and Type | Method and Description |
|---|---|
ImputerModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<String> |
inputCol()
Param for input column name.
|
StringArrayParam |
inputCols()
Param for input column names.
|
static ImputerModel |
load(String path) |
DoubleParam |
missingValue()
The placeholder for the missing values.
|
Param<String> |
outputCol()
Param for output column name.
|
StringArrayParam |
outputCols()
Param for output column names.
|
static MLReader<ImputerModel> |
read() |
DoubleParam |
relativeError()
Param for the relative target precision for the approximate quantile algorithm.
|
ImputerModel |
setInputCol(String value) |
ImputerModel |
setInputCols(String[] value) |
ImputerModel |
setOutputCol(String value) |
ImputerModel |
setOutputCols(String[] value) |
Param<String> |
strategy()
The imputation strategy.
|
Dataset<Row> |
surrogateDF() |
String |
toString() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transformparamsgetInOutCols, getMissingValue, getStrategy, validateAndTransformSchemagetInputColgetInputColsgetOutputColgetOutputColsgetRelativeErrorclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnsave$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic static MLReader<ImputerModel> read()
public static ImputerModel load(String path)
public final Param<String> strategy()
ImputerParamsstrategy in interface ImputerParamspublic final DoubleParam missingValue()
ImputerParamsmissingValue in interface ImputerParamspublic final DoubleParam relativeError()
HasRelativeErrorrelativeError in interface HasRelativeErrorpublic final StringArrayParam outputCols()
HasOutputColsoutputCols in interface HasOutputColspublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final StringArrayParam inputCols()
HasInputColsinputCols in interface HasInputColspublic final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic String uid()
Identifiableuid in interface Identifiablepublic ImputerModel setInputCol(String value)
public ImputerModel setOutputCol(String value)
public ImputerModel setInputCols(String[] value)
public ImputerModel setOutputCols(String[] value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformertransform in class Transformerdataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
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 ImputerModel copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Model<ImputerModel>extra - (undocumented)public MLWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritablepublic String toString()
toString in interface IdentifiabletoString in class Object