public class Imputer extends Estimator<ImputerModel> implements ImputerParams, DefaultParamsWritable
Note that the mean/median value is computed after filtering out missing values. All Null values in the input columns are treated as missing, and so are also imputed. For computing median, DataFrameStatFunctions.approxQuantile is used with a relative error of 0.001.
| Modifier and Type | Method and Description |
|---|---|
Imputer |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
ImputerModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
static Imputer |
load(String path) |
static MLReader<T> |
read() |
Imputer |
setInputCols(String[] value) |
Imputer |
setMissingValue(double value) |
Imputer |
setOutputCols(String[] value) |
Imputer |
setStrategy(String value)
Imputation strategy.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetMissingValue, getStrategy, missingValue, strategy, validateAndTransformSchemagetInputCols, inputColsgetOutputCols, outputColsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static Imputer load(String path)
public static MLReader<T> read()
public String uid()
Identifiableuid in interface Identifiablepublic Imputer setInputCols(String[] value)
public Imputer setOutputCols(String[] value)
public Imputer setStrategy(String value)
value - (undocumented)public Imputer setMissingValue(double value)
public ImputerModel fit(Dataset<?> dataset)
Estimatorfit in class Estimator<ImputerModel>dataset - (undocumented)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 Imputer copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Estimator<ImputerModel>extra - (undocumented)