- <init>
Simply initializes #weights.
- clear
Empties the weight map.
- clone
Returns a copy of this SparseWeightVector in which the #weights variable has
been cloned deeply.
- dot
Takes the dot product of this SparseWeightVector with the argument vector, using
the specified defau
- getRawWeights
For those cases where we need the raw weights (during model optimization).
- getWeight
Returns the weight of the given feature.
- pairwiseMultiply
The strength of each feature in the argument vector is multiplied by the
corresponding weight in thi
- pruneWeights
delete all irrelevant feature weights.
- read
Reads the representation of a weight vector with this object's run-time type
from the given stream,
- readWeightVector
Reads the binary representation of a weight vector of any type from the given
stream. The stream is
- scaledAdd
- scaledMultiply
Self-modifying vector multiplication where the argument vector is first scaled
by the given factor.