BinaryEncoderModel

Instance Constructors

new BinaryEncoderModel(uid: String, categorySizes: Array[Int])

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
val categorySizes: Array[Int]
final def clear(param: Param[_]): BinaryEncoderModel.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def copy(extra: ParamMap): BinaryEncoderModel

Definition Classes
BinaryEncoderModel → Model → Transformer → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getHandleInvalid: String

Definition Classes
HasHandleInvalid
final def getInputCols: Array[String]

Definition Classes
HasInputCols
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
final def getOutputCols: Array[String]

Definition Classes
HasOutputCols
def getParam(paramName: String): Param[Any]

Definition Classes
Params
val handleInvalid: Param[String]

Configuration of the Parameter for handling invalid entries in a previously modeled feature column.
Configuration of the Parameter for handling invalid entries in a previously modeled feature column.

Definition Classes
BinaryEncoderBase → HasHandleInvalid
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hasParent: Boolean

Definition Classes
Model
def hashCode(): Int

Definition Classes
AnyRef → Any
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final val inputCols: StringArrayParam

Definition Classes
HasInputCols
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
final val outputCols: StringArrayParam

Definition Classes
HasOutputCols
lazy val params: Array[Param[_]]

Definition Classes
Params
var parent: Estimator[BinaryEncoderModel]

Definition Classes
Model
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
final def set(paramPair: ParamPair[_]): BinaryEncoderModel.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): BinaryEncoderModel.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): BinaryEncoderModel.this.type

Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): BinaryEncoderModel.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): BinaryEncoderModel.this.type

Attributes
protected
Definition Classes
Params
def setHandleInvalid(value: String): BinaryEncoderModel.this.type

Setter for whether to allow for unseen indexed nominal values to be used in the transformation of a dataset with the generated BinaryEncoderModel.
Setter for whether to allow for unseen indexed nominal values to be used in the transformation of a dataset with the generated BinaryEncoderModel.
value
The setting to be used: either 'keep' or 'error'

Since
0.5.3
Note
Default: 'error' optional settings: 'keep' or 'error'
def setInputCols(values: Array[String]): BinaryEncoderModel.this.type

Setter for specifying the column names in Array format for the columns intended to be Binary Indexed.
Setter for specifying the column names in Array format for the columns intended to be Binary Indexed.
values
Array of column names

Since
0.5.3
def setOutputCols(values: Array[String]): BinaryEncoderModel.this.type

Setter for specifying the desired output columns in Array format for the columns to be generated as Breeze DenseVectors when the model is used to transform a dataset
Setter for specifying the desired output columns in Array format for the columns to be generated as Breeze DenseVectors when the model is used to transform a dataset
values
Array of output column names

Since
0.5.3
Note
the index position relationship between setInputCols and setOutputCols is a 1 to 1 relationship. The positional order and length must be congruent and match.
def setParent(parent: Estimator[BinaryEncoderModel]): BinaryEncoderModel

Definition Classes
Model
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def transform(dataset: Dataset[_]): DataFrame

Main transformation method that will apply the model's configured encoding through a udf to the input dataset and add encoded columns.
Main transformation method that will apply the model's configured encoding through a udf to the input dataset and add encoded columns.
dataset
input dataset for the model to mutate
returns
a DataFrame with added BinaryEncoded columns

Definition Classes
BinaryEncoderModel → Transformer
Since
0.5.3
def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

Definition Classes
Transformer
Annotations
@Since( "2.0.0" )
def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

Definition Classes
Transformer
Annotations
@Since( "2.0.0" ) @varargs()
def transformSchema(schema: StructType): StructType

Method for mutating the dataset schema to support the addition of BinaryEncoded columns
Method for mutating the dataset schema to support the addition of BinaryEncoded columns
schema
the schema of the dataset

Definition Classes
BinaryEncoderModel → PipelineStage
Since
0.5.3
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
BinaryEncoderModel → Identifiable
def validateAndTransformSchema(schema: StructType, keepInvalid: Boolean): StructType

Method for validating the resultant schema from the application of building and transforming using this encoder package.
Method for validating the resultant schema from the application of building and transforming using this encoder package. The purpose of validation is to ensure that the supplied input columns are of the correct binary or nominal (ordinal numeric) type and that the output columns will contain the correct number of columns based on the configuration set.
schema
The schema of the dataset supplied for training of the model or used in transforming using the model
keepInvalid
Boolean flag for whether to allow for an additional binary encoding value to be used for any values that were unknown at the time of model training, which will summarily be converted to a 'max binary value' of the encoding length + 1 with maximum n * "1" values.
returns
StructType that represents the transformed schema with additional output columns appended to the dataset structure.

Attributes
protected
Definition Classes
BinaryEncoderBase
Annotations
@throws( ... )
Since
0.5.3
Exceptions thrown
UnsupportedOperationException if the configured input cols and output cols do not match one another in length.
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def write: MLWriter

Definition Classes
BinaryEncoderModel → MLWritable

Related Docs: object BinaryEncoderModel | package feature

class BinaryEncoderModel extends Model[BinaryEncoderModel] with BinaryEncoderBase with MLWritable

Instance Constructors

new BinaryEncoderModel(uid: String, categorySizes: Array[Int])

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val categorySizes: Array[Int]

final def clear(param: Param[_]): BinaryEncoderModel.this.type

def clone(): AnyRef

def copy(extra: ParamMap): BinaryEncoderModel

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

def finalize(): Unit

final def get[T](param: Param[T]): Option[T]

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

final def getHandleInvalid: String

final def getInputCols: Array[String]

final def getOrDefault[T](param: Param[T]): T

final def getOutputCols: Array[String]

def getParam(paramName: String): Param[Any]

val handleInvalid: Param[String]

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hasParent: Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final val inputCols: StringArrayParam

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val outputCols: StringArrayParam

lazy val params: Array[Param[_]]

var parent: Estimator[BinaryEncoderModel]

def save(path: String): Unit

final def set(paramPair: ParamPair[_]): BinaryEncoderModel.this.type

final def set(param: String, value: Any): BinaryEncoderModel.this.type

final def set[T](param: Param[T], value: T): BinaryEncoderModel.this.type

final def setDefault(paramPairs: ParamPair[_]*): BinaryEncoderModel.this.type

final def setDefault[T](param: Param[T], value: T): BinaryEncoderModel.this.type

def setHandleInvalid(value: String): BinaryEncoderModel.this.type

def setInputCols(values: Array[String]): BinaryEncoderModel.this.type

def setOutputCols(values: Array[String]): BinaryEncoderModel.this.type

def setParent(parent: Estimator[BinaryEncoderModel]): BinaryEncoderModel

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def transform(dataset: Dataset[_]): DataFrame

def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

def transformSchema(schema: StructType): StructType

def transformSchema(schema: StructType, logging: Boolean): StructType

val uid: String