K-Index

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes|All Packages

K

k - Variable in class es.uam.eps.ir.relison.links.data.letor.sampling.RecommenderIndividualSampler: The cutoff of the recommendation.
k - Variable in class es.uam.eps.ir.relison.links.data.ml.balance.SMOTEBalancer: Number of neighbours.
k - Variable in class es.uam.eps.ir.relison.links.recommendation.algorithms.knn.similarities.ir.BM25Similarity: Parameter of the algorithm that tunes the effect of the weight
k - Variable in class es.uam.eps.ir.relison.links.recommendation.algorithms.standalone.ir.BM25: Parameter that tunes the effect of the term frequency on the formula.
k - Variable in class es.uam.eps.ir.relison.links.recommendation.algorithms.standalone.pathbased.LocalPathIndex: The maximum distance between users.
k - Variable in class es.uam.eps.ir.relison.links.recommendation.updateable.ir.UpdateableBM25: Parameter that tunes the effect of the term frequency on the formula.
k - Variable in class es.uam.eps.ir.relison.links.recommendation.updateable.knn.user.UpdateableUBkNN: The number of neighbors to select.
k - Variable in class es.uam.eps.ir.relison.sna.community.clustering.KMeans: The number of desired clusters.
k - Variable in class es.uam.eps.ir.relison.sna.community.detection.modularity.balanced.SpectralClustering: The number of clusters we want to find.
K - Static variable in class es.uam.eps.ir.relison.grid.community.modularity.balanced.NormalizedCutSpectralClusteringConfigurator: Identifier for the desired number of communities
K - Static variable in class es.uam.eps.ir.relison.grid.community.modularity.balanced.RatioCutSpectralClusteringConfigurator: Identifier for the desired number of communities
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.knn.ItemBasedCFGridSearch: Identifier for the number of neighbors of the algorithm.
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.knn.UserBasedCFGridSearch: Identifier for the number of neighbors of the algorithm.
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.ir.BM25GridSearch: Identifier for parameter k
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.mf.FastImplicitMFGridSearch: Identifier for indicating if teleport always goes to the origin node.
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.mf.ImplicitMFGridSearch: Identifier for the number of latent factors.
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.pathbased.LocalPathIndexGridSearch: Identifier for the maximum distance from the target to the candidate users.
K - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.sampling.RecommenderIndividualSamplerConfigurator: Identifier for the cutoff of the recommendation.
K - Variable in class es.uam.eps.ir.relison.links.recommendation.updateable.mf.UpdateableFactorization: dimensionality of the vector space
Katz - Class in es.uam.eps.ir.relison.links.recommendation.algorithms.standalone.pathbased: Katz algorithm.
Katz(FastGraph, double) - Constructor for class es.uam.eps.ir.relison.links.recommendation.algorithms.standalone.pathbased.Katz: Constructor.
Katz(FastGraph, double, EdgeOrientation) - Constructor for class es.uam.eps.ir.relison.links.recommendation.algorithms.standalone.pathbased.Katz: Constructor.
KATZ - Static variable in class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.AlgorithmIdentifiers: Identifier for the Katz algorithm.
KATZ - Static variable in class es.uam.eps.ir.relison.grid.sna.vertex.VertexMetricIdentifiers: Identifier for the Katz centrality.
KatzCentrality - Class in es.uam.eps.ir.relison.sna.metrics.vertex: Finds the Katz centrality of the nodes, which estimates the importance of a node considering the paths between the node and the rest of the network.
KatzCentrality(double) - Constructor for class es.uam.eps.ir.relison.sna.metrics.vertex.KatzCentrality: Constructor.
KatzCentrality(EdgeOrientation, double) - Constructor for class es.uam.eps.ir.relison.sna.metrics.vertex.KatzCentrality: Constructor.
KatzCentrality(MatrixLibrary, double) - Constructor for class es.uam.eps.ir.relison.sna.metrics.vertex.KatzCentrality: Constructor.
KatzCentrality(MatrixLibrary, EdgeOrientation, double) - Constructor for class es.uam.eps.ir.relison.sna.metrics.vertex.KatzCentrality: Constructor.
KatzCentralityGridSearch - Class in es.uam.eps.ir.relison.grid.sna.vertex: Grid for the Katz centrality of a node.
KatzCentralityGridSearch() - Constructor for class es.uam.eps.ir.relison.grid.sna.vertex.KatzCentralityGridSearch
KatzGridSearch - Class in es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.pathbased: Grid search generator for Katz algorithm.
KatzGridSearch() - Constructor for class es.uam.eps.ir.relison.grid.links.recommendation.algorithms.standalone.pathbased.KatzGridSearch
KLD - Static variable in class es.uam.eps.ir.relison.grid.diffusion.metrics.MetricIdentifiers: Identifier for the individual feature KL divergence metric.
KLDivergence - Class in es.uam.eps.ir.relison.utils.indexes: Computes the KL divergence as a distance between two distributions (an original one, P(x), and an estimated one from real data Q(x).
KLDivergence() - Constructor for class es.uam.eps.ir.relison.utils.indexes.KLDivergence
KMeans - Class in es.uam.eps.ir.relison.sna.community.clustering: Implementation of the k-means clustering algorithm.
KMeans(int) - Constructor for class es.uam.eps.ir.relison.sna.community.clustering.KMeans: Constructor.

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes|All Packages