public class StringIndexerModel extends Model<StringIndexerModel> implements MLWritable
StringIndexer
.
NOTE: During transformation, if the input column does not exist,
StringIndexerModel.transform
would return the input dataset unmodified.
This is a temporary fix for the case when target labels do not exist during prediction.
param: labels Ordered list of labels, corresponding to indices to be assigned.
Constructor and Description |
---|
StringIndexerModel(java.lang.String[] labels) |
StringIndexerModel(java.lang.String uid,
java.lang.String[] labels) |
Modifier and Type | Method and Description |
---|---|
StringIndexerModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
java.lang.String |
getHandleInvalid() |
java.lang.String |
getInputCol() |
java.lang.String |
getOutputCol() |
Param<java.lang.String> |
handleInvalid()
Param for how to handle invalid entries.
|
Param<java.lang.String> |
inputCol()
Param for input column name.
|
java.lang.String[] |
labels() |
static StringIndexerModel |
load(java.lang.String path) |
Param<java.lang.String> |
outputCol()
Param for output column name.
|
static MLReader<StringIndexerModel> |
read() |
StringIndexerModel |
setHandleInvalid(java.lang.String value) |
StringIndexerModel |
setInputCol(java.lang.String value) |
StringIndexerModel |
setOutputCol(java.lang.String value) |
DataFrame |
transform(DataFrame dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
java.lang.String |
uid()
An immutable unique ID for the object and its derivatives.
|
StructType |
validateAndTransformSchema(StructType schema)
Validates and transforms the input schema.
|
org.apache.spark.ml.feature.StringIndexerModel.StringIndexModelWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
transformSchema
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams
toString
save
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public StringIndexerModel(java.lang.String uid, java.lang.String[] labels)
public StringIndexerModel(java.lang.String[] labels)
public static MLReader<StringIndexerModel> read()
public static StringIndexerModel load(java.lang.String path)
public java.lang.String uid()
Identifiable
uid
in interface Identifiable
public java.lang.String[] labels()
public StringIndexerModel setHandleInvalid(java.lang.String value)
public StringIndexerModel setInputCol(java.lang.String value)
public StringIndexerModel setOutputCol(java.lang.String value)
public DataFrame transform(DataFrame dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
Derives the output schema from the input schema.
transformSchema
in class PipelineStage
schema
- (undocumented)public StringIndexerModel copy(ParamMap extra)
Params
copy
in interface Params
copy
in class Model<StringIndexerModel>
extra
- (undocumented)defaultCopy()
public org.apache.spark.ml.feature.StringIndexerModel.StringIndexModelWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public StructType validateAndTransformSchema(StructType schema)
public Param<java.lang.String> inputCol()
public java.lang.String getInputCol()
public Param<java.lang.String> outputCol()
public java.lang.String getOutputCol()
public Param<java.lang.String> handleInvalid()
public java.lang.String getHandleInvalid()