public class ColumnPruner extends Transformer implements MLWritable
Constructor and Description |
---|
ColumnPruner(scala.collection.immutable.Set<String> columnsToPrune) |
ColumnPruner(String uid,
scala.collection.immutable.Set<String> columnsToPrune) |
Modifier and Type | Method and Description |
---|---|
scala.collection.immutable.Set<String> |
columnsToPrune() |
ColumnPruner |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static ColumnPruner |
load(String path) |
static MLReader<ColumnPruner> |
read() |
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
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
save
clear, copyValues, defaultCopy, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, set, set, set, setDefault, setDefault, shouldOwn
toString
$init$, 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 ColumnPruner(String uid, scala.collection.immutable.Set<String> columnsToPrune)
public ColumnPruner(scala.collection.immutable.Set<String> columnsToPrune)
public static MLReader<ColumnPruner> read()
public static ColumnPruner load(String path)
public String uid()
Identifiable
uid
in interface Identifiable
public scala.collection.immutable.Set<String> columnsToPrune()
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 ColumnPruner copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Transformer
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable