NormContinuous

class NormContinuous(val linearNorms: Array[LinearNorm], val field: Field, val mapMissingTo: Option[Double], val outliers: OutlierTreatmentMethod) extends NumericFieldExpression

Normalization provides a basic framework for mapping input values to specific value ranges, usually the numeric range [0 .. 1]. Normalization is used, e.g., in neural networks and clustering models.

Defines how to normalize an input field by piecewise linear interpolation. The mapMissingTo attribute defines the value the output is to take if the input is missing. If the mapMissingTo attribute is not specified, then missing input values produce a missing result.

trait Evaluator
trait Serializable
class Object
trait Matchable
class Any

Value members

Concrete methods

override def deeval(input: Any): Double
Definition Classes
override def eval(series: Series): Double

Inherited methods

def categories: Array[Any]
Inherited from:
Expression
override def child: FieldRef
Definition Classes
Inherited from:
FieldExpression
final override def children: Array[Expression]
Definition Classes
Inherited from:
UnaryExpression
def eval(value: Any): Any
Inherited from:
Expression
Inherited from:
HasExtensions
override def getDataField: Option[Field]
Definition Classes
Inherited from:
FieldExpression
def hasExtensions: Boolean
Inherited from:
HasExtensions

Concrete fields

val mapMissingTo: Option[Double]