Index (clustering 15.0.0-beta3 API)

A

apply(double[]) - Method in class com.linkedin.dagli.clustering.NearestDoubleArray

getPreparer(PreparerContext) - Method in class com.linkedin.dagli.clustering.KMeansCluster

KMeansCluster - Class in com.linkedin.dagli.clustering: Clusters vectors into k groups via the KMeans++ algorithm and generates the [0, k-1] cluster assignment for each vector.
KMeansCluster() - Constructor for class com.linkedin.dagli.clustering.KMeansCluster: Creates a new KMeans clusterer with k = 10 and unlimited iterations.
KMeansCluster(int) - Constructor for class com.linkedin.dagli.clustering.KMeansCluster: Creates a new KMeans clusterer with the specified value of k and unlimited iterations.

NearestDoubleArray - Class in com.linkedin.dagli.clustering: NearestDoubleArray finds the array that is "closest" (as determined by Euclidean distance) to an input array from a pre-determined list of candidates.
NearestDoubleArray() - Constructor for class com.linkedin.dagli.clustering.NearestDoubleArray

validate() - Method in class com.linkedin.dagli.clustering.NearestDoubleArray

withCandidates(List<double[]>) - Method in class com.linkedin.dagli.clustering.NearestDoubleArray: Sets the candidate vectors.
withInput() - Method in class com.linkedin.dagli.clustering.KMeansCluster
withInput(Producer<? extends DenseVector>) - Method in class com.linkedin.dagli.clustering.KMeansCluster: Creates a copy of this instance that will obtain DenseVector inputs from the specified Producer.
withInputArray(Producer<? extends double[]>) - Method in class com.linkedin.dagli.clustering.KMeansCluster: Creates a copy of this instance that will obtain its inputs from the specified Producer of double arrays.
withK(int) - Method in class com.linkedin.dagli.clustering.KMeansCluster: Sets the number of clusters that will be computed.
withMaxIterations(int) - Method in class com.linkedin.dagli.clustering.KMeansCluster: Returns a copy of this KMeansCluster transformer with the specified number of maximum iterations that will be used to optimize the clusters.
withSeed(long) - Method in class com.linkedin.dagli.clustering.KMeansCluster: Sets the random seed (by default, 0) used for initialization.