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, transform
params
getInOutCols, getMissingValue, getStrategy, validateAndTransformSchema
getInputCol
getInputCols
getOutputCol
getOutputCols
getRelativeError
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
save
$init$, 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_, uninitialize
public static MLReader<ImputerModel> read()
public static ImputerModel load(String path)
public final Param<String> strategy()
ImputerParams
strategy
in interface ImputerParams
public final DoubleParam missingValue()
ImputerParams
missingValue
in interface ImputerParams
public final DoubleParam relativeError()
HasRelativeError
relativeError
in interface HasRelativeError
public final StringArrayParam outputCols()
HasOutputCols
outputCols
in interface HasOutputCols
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public final StringArrayParam inputCols()
HasInputCols
inputCols
in interface HasInputCols
public final Param<String> inputCol()
HasInputCol
inputCol
in interface HasInputCol
public String uid()
Identifiable
uid
in interface Identifiable
public 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)
Transformer
transform
in class Transformer
dataset
- (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 PipelineStage
schema
- (undocumented)public ImputerModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<ImputerModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public String toString()
toString
in interface Identifiable
toString
in class Object