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.
|
static ImputerModel |
load(String path) |
static MLReader<ImputerModel> |
read() |
ImputerModel |
setInputCols(String[] value) |
ImputerModel |
setOutputCols(String[] value) |
Dataset<Row> |
surrogateDF() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transformequals, 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, shouldOwntoStringsaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static MLReader<ImputerModel> read()
public static ImputerModel load(String path)
public String uid()
Identifiableuid in interface Identifiablepublic 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)
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 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 MLWritable