public class OneHotEncoderModel extends Model<OneHotEncoderModel> implements OneHotEncoderBase, MLWritable
Modifier and Type | Method and Description |
---|---|
int[] |
categorySizes() |
OneHotEncoderModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static OneHotEncoderModel |
load(String path) |
static MLReader<OneHotEncoderModel> |
read() |
OneHotEncoderModel |
setDropLast(boolean value) |
OneHotEncoderModel |
setHandleInvalid(String value) |
OneHotEncoderModel |
setInputCols(String[] values) |
OneHotEncoderModel |
setOutputCols(String[] values) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
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
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
dropLast, getDropLast, handleInvalid, validateAndTransformSchema
getHandleInvalid
getInputCols, inputCols
getOutputCols, outputCols
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString
save
initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public static MLReader<OneHotEncoderModel> read()
public static OneHotEncoderModel load(String path)
public String uid()
Identifiable
uid
in interface Identifiable
public int[] categorySizes()
public OneHotEncoderModel setInputCols(String[] values)
public OneHotEncoderModel setOutputCols(String[] values)
public OneHotEncoderModel setDropLast(boolean value)
public OneHotEncoderModel setHandleInvalid(String value)
public StructType transformSchema(StructType schema)
PipelineStage
Check transform validity and derive the output schema from the input schema.
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 Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public OneHotEncoderModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<OneHotEncoderModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable