public final class IDF extends Estimator<IDFModel> implements IDFBase, DefaultParamsWritable
| Modifier and Type | Method and Description |
|---|---|
IDF |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
IDFModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
inputCol()
Param for input column name.
|
static IDF |
load(String path) |
IntParam |
minDocFreq()
The minimum number of documents in which a term should appear.
|
Param<String> |
outputCol()
Param for output column name.
|
static MLReader<T> |
read() |
IDF |
setInputCol(String value) |
IDF |
setMinDocFreq(int value) |
IDF |
setOutputCol(String value) |
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.
|
paramsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetMinDocFreq, validateAndTransformSchemagetInputColgetOutputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesave$init$, 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 IDF load(String path)
public static MLReader<T> read()
public final IntParam minDocFreq()
IDFBaseminDocFreq in interface IDFBasepublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic String uid()
Identifiableuid in interface Identifiablepublic IDF setInputCol(String value)
public IDF setOutputCol(String value)
public IDF setMinDocFreq(int value)
public IDFModel fit(Dataset<?> dataset)
Estimatorpublic 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)