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package knn

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Type Members

  1. trait DistanceFunction extends AnyRef

Value Members

  1. def classification(values: Vec[Int], indices: Mat[Int], numClasses: Int, log: Boolean): Mat[Double]
  2. def jaccardDistance(v1: STen, v2: STen)(implicit scope: Scope): STen
  3. def knn(d: STen, query: STen, k: Int, distanceMatrix: DistanceFunction)(implicit scope: Scope): STen
  4. 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]
  5. def knnMinibatched(d: STen, query: STen, k: Int, distanceMatrix: DistanceFunction, minibatchSize: Int)(implicit scope: Scope): STen
  6. 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]
  7. def knnSearch(features: Mat[Double], query: Mat[Double], k: Int, distance: DistanceFunction, device: Device, precision: FloatingPointPrecision, minibatchSize: Int): Mat[Int]
  8. def regression(values: Vec[Double], indices: Mat[Int]): Vec[Double]
  9. def squaredEuclideanDistance(v1: STen, v2: STen)(implicit scope: Scope): STen
  10. object JaccardDistance extends DistanceFunction
  11. object SquaredEuclideanDistance extends DistanceFunction

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