GaussianMixtureModel

new GaussianMixtureModel(gaussianLawFeaturesSortedByClusterID: Array[GaussianLawFeatures], πksortedByClusterID: Map[Int, Double])

final def !=(arg0: Any): Boolean

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

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val algorithmID: GaussianMixtures.type

Definition Classes
GaussianMixtureModel → ClusteringModel
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate() @throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val gaussianLawFeaturesSortedByClusterID: Array[GaussianLawFeatures]
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
def predict(gs: GenSeq[DenseVector[Double]]): GenSeq[Int]
def predict(v: DenseVector[Double]): Int
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(arg0: Long, arg1: Int): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )
val πksortedByClusterID: Map[Int, Double]