Uses of Interface
de.lmu.ifi.dbs.elki.data.SparseFeatureVector

Packages that use SparseFeatureVector

Package	Description
de.lmu.ifi.dbs.elki.algorithm.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types.

Uses of SparseFeatureVector in de.lmu.ifi.dbs.elki.algorithm.itemsetmining

Method parameters in de.lmu.ifi.dbs.elki.algorithm.itemsetmining with type arguments of type SparseFeatureVector

Modifier and Type	Method and Description
protected List<OneItemset>	APRIORI.buildFrequentOneItemsets(Relation<? extends SparseFeatureVector<?>> relation, int dim, int needed) Build the 1-itemsets.

Uses of SparseFeatureVector in de.lmu.ifi.dbs.elki.data

Subinterfaces of SparseFeatureVector in de.lmu.ifi.dbs.elki.data

Modifier and Type	Interface and Description
interface	SparseNumberVector Combines the SparseFeatureVector and NumberVector.

Classes in de.lmu.ifi.dbs.elki.data that implement SparseFeatureVector

Modifier and Type	Class and Description
class	BitVector Vector using a dense bit set encoding, based on long[] storage.
class	SparseByteVector Sparse vector type, using byte[] for storing the values, and int[] for storing the indexes, approximately 5 bytes per non-zero value (limited to -128..+127).
class	SparseDoubleVector Sparse vector type, using double[] for storing the values, and int[] for storing the indexes, approximately 12 bytes per non-zero value.
class	SparseFloatVector Sparse vector type, using float[] for storing the values, and int[] for storing the indexes, approximately 8 bytes per non-zero value.
class	SparseIntegerVector Sparse vector type, using int[] for storing the values, and int[] for storing the indexes, approximately 8 bytes per non-zero integer value.
class	SparseShortVector Sparse vector type, using short[] for storing the values, and int[] for storing the indexes, approximately 6 bytes per non-zero value.