lamp-knn
API
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lamp-knn/lamp.knn

lamp.knn

package lamp.knn

Members list

Type members

Classlikes

trait DistanceFunction

Attributes

Supertypes
class Object
trait Matchable
class Any
Known subtypes
object JaccardDistance.type
object JaccardDistance extends DistanceFunction

Attributes

Supertypes
class Object
trait Matchable
class Any
Self type
object SquaredEuclideanDistance extends DistanceFunction

Attributes

Supertypes
class Object
trait Matchable
class Any
Self type

Value members

Concrete methods

def classification(values: Vec[Int], indices: Mat[Int], numClasses: Int, log: Boolean): Mat[Double]
def jaccardDistance(v1: STen, v2: STen)(implicit scope: Scope): STen
def knn(d: STen, query: STen, k: Int, distanceMatrix: DistanceFunction)(implicit scope: Scope): STen
def knnClassification(features: Mat[Double], values: Vec[Int], query: Mat[Double], k: Int, distance: DistanceFunction, device: Device, precision: FloatingPointPrecision, minibatchSize: Int, log: Boolean): Mat[Double]
def knnMinibatched(d: STen, query: STen, k: Int, distanceMatrix: DistanceFunction, minibatchSize: Int)(implicit scope: Scope): STen
def knnRegression(features: Mat[Double], values: Vec[Double], query: Mat[Double], k: Int, distance: DistanceFunction, device: Device, precision: FloatingPointPrecision, minibatchSize: Int): Vec[Double]
def knnSearch(features: Mat[Double], query: Mat[Double], k: Int, distance: DistanceFunction, device: Device, precision: FloatingPointPrecision, minibatchSize: Int): Mat[Int]
def regression(values: Vec[Double], indices: Mat[Int]): Vec[Double]
def squaredEuclideanDistance(v1: STen, v2: STen)(implicit scope: Scope): STen
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