package knn
Value Members
- 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 = CPU, precision: FloatingPointPrecision = DoublePrecision, minibatchSize: Int = Int.MaxValue): 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
- object JaccardDistance extends DistanceFunction
- object SquaredEuclideanDistance extends DistanceFunction
Inherited from AnyRef
Inherited from Any