Serializable
, org.apache.spark.internal.Logging
, ClassifierParams
, ClassifierTypeTrait
, OneVsRestParams
, Params
, HasFeaturesCol
, HasLabelCol
, HasParallelism
, HasPredictionCol
, HasRawPredictionCol
, HasWeightCol
, PredictorParams
, Identifiable
, MLWritable
Reduction of Multiclass Classification to Binary Classification. Performs reduction using one against all strategy. For a multiclass classification with k classes, train k models (one per class). Each example is scored against all k models and the model with highest score is picked to label the example.
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
Constructors
param for the base binary classifier that we reduce multiclass classification into.
Creates a copy of this instance with the same UID and some extra params.
Param for features column name.
Fits a model to the input data.
Param for label column name.
The number of threads to use when running parallel algorithms.
Param for prediction column name.
Param for raw prediction (a.k.a.
The implementation of parallel one vs.
Check transform validity and derive the output schema from the input schema.
An immutable unique ID for the object and its derivatives.
Param for weight column name.
Returns an MLWriter
instance for this ML instance.
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
Methods inherited from interface org.apache.spark.ml.util.MLWritablesave
Methods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
public OneVsRest()
parallelism
in interface HasParallelism
param for the base binary classifier that we reduce multiclass classification into. The base classifier input and output columns are ignored in favor of the ones specified in
OneVsRest
.
classifier
in interface OneVsRestParams
Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.
weightCol
in interface HasWeightCol
Param for raw prediction (a.k.a. confidence) column name.
rawPredictionCol
in interface HasRawPredictionCol
Param for prediction column name.
predictionCol
in interface HasPredictionCol
Param for features column name.
featuresCol
in interface HasFeaturesCol
Param for label column name.
labelCol
in interface HasLabelCol
An immutable unique ID for the object and its derivatives.
uid
in interface Identifiable
value
- (undocumented)
Sets the value of param
weightCol()
.
This is ignored if weight is not supported by classifier()
. If this is not set or empty, we treat all instance weights as 1.0. Default is not set, so all instances have weight one.
value
- (undocumented)
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)
Fits a model to the input data.
fit
in class Estimator<OneVsRestModel>
dataset
- (undocumented)
Params
Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy()
.
copy
in interface Params
copy
in class Estimator<OneVsRestModel>
extra
- (undocumented)
Returns an MLWriter
instance for this ML instance.
write
in interface MLWritable
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