public class OneHotEncoder extends Transformer
[0.0, 0.0, 1.0, 0.0]
.
The last category is not included by default (configurable via OneHotEncoder!.dropLast
because it makes the vector entries sum up to one, and hence linearly dependent.
So an input value of 4.0 maps to [0.0, 0.0, 0.0, 0.0]
.
Note that this is different from scikit-learn's OneHotEncoder, which keeps all categories.
The output vectors are sparse.
StringIndexer} for converting categorical values into category indices
,
Serialized FormConstructor and Description |
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OneHotEncoder() |
OneHotEncoder(java.lang.String uid) |
Modifier and Type | Method and Description |
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OneHotEncoder |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
BooleanParam |
dropLast()
Whether to drop the last category in the encoded vector (default: true)
|
OneHotEncoder |
setDropLast(boolean value) |
OneHotEncoder |
setInputCol(java.lang.String value) |
OneHotEncoder |
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.
|
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
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public OneHotEncoder(java.lang.String uid)
public OneHotEncoder()
public java.lang.String uid()
Identifiable
public final BooleanParam dropLast()
public OneHotEncoder setDropLast(boolean value)
public OneHotEncoder setInputCol(java.lang.String value)
public OneHotEncoder setOutputCol(java.lang.String value)
public StructType transformSchema(StructType schema)
PipelineStage
Derives the output schema from the input schema.
transformSchema
in class PipelineStage
schema
- (undocumented)public DataFrame transform(DataFrame dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public OneHotEncoder copy(ParamMap extra)
Params
copy
in interface Params
copy
in class Transformer
extra
- (undocumented)defaultCopy()