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 |
|---|
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, transformparamsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitsaveclear, copyValues, defaultCopy, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, set, set, set, setDefault, setDefault, shouldOwntoString$init$, 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 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()
Identifiableuid in interface Identifiablepublic String vectorCol()
public scala.collection.immutable.Map<String,String> prefixesToRewrite()
public Dataset<Row> transform(Dataset<?> dataset)
Transformertransform in class Transformerdataset - (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 PipelineStageschema - (undocumented)public VectorAttributeRewriter copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Transformerextra - (undocumented)public MLWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritable