public class VectorAttributeRewriter extends Transformer implements MLWritable
param: vectorCol name of the vector column to rewrite. param: prefixesToRewrite the map of string prefixes to their replacement values. Each attribute name defined in vectorCol will be checked against the keys of this map. When a key prefixes a name, the matching prefix will be replaced by the value in the map.
Constructor and Description |
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VectorAttributeRewriter(String vectorCol,
scala.collection.immutable.Map<String,String> prefixesToRewrite) |
VectorAttributeRewriter(String uid,
String vectorCol,
scala.collection.immutable.Map<String,String> prefixesToRewrite) |
Modifier and Type | Method and Description |
---|---|
VectorAttributeRewriter |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static VectorAttributeRewriter |
load(String path) |
scala.collection.immutable.Map<String,String> |
prefixesToRewrite() |
static MLReader<VectorAttributeRewriter> |
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.
|
String |
vectorCol() |
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 VectorAttributeRewriter(String uid, String vectorCol, scala.collection.immutable.Map<String,String> prefixesToRewrite)
public VectorAttributeRewriter(String vectorCol, scala.collection.immutable.Map<String,String> prefixesToRewrite)
public static MLReader<VectorAttributeRewriter> read()
public static VectorAttributeRewriter load(String path)
public String uid()
Identifiable
uid
in interface Identifiable
public String vectorCol()
public scala.collection.immutable.Map<String,String> prefixesToRewrite()
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 VectorAttributeRewriter 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