Uses of Class
de.lmu.ifi.dbs.elki.data.AbstractNumberVector

Packages that use AbstractNumberVector

Package	Description
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types.

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

Classes in de.lmu.ifi.dbs.elki.data with type parameters of type AbstractNumberVector

Modifier and Type	Class and Description
static class	AbstractNumberVector.Factory<V extends AbstractNumberVector> Factory class.

Subclasses of AbstractNumberVector in de.lmu.ifi.dbs.elki.data

Modifier and Type	Class and Description
class	BitVector Vector using a dense bit set encoding, based on long[] storage.
class	ByteVector Vector using byte[] storage.
class	DoubleVector Vector type using double[] storage for real numbers.
class	FloatVector Vector type using float[] storage, thus needing approximately half as much memory as DoubleVector.
class	IntegerVector Vector type using int[] storage.
class	OneDimensionalDoubleVector Specialized class implementing a one-dimensional double vector without using an array.
class	ShortVector Vector type using short[] 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.