if true, include indices when hashing a feature that has them (OPLists or OPVectors)
if true, prepends a input feature name to each token of that feature
number of features (hashes) to generate
number of inputs
max number of features (hashes)
if true, term frequency vector will be binary such that non-zero term counts will be set to 1.0
hash algorithm to use
strategy to determine whether to use shared hash space for all included features
if true, term frequency vector will be binary such that non-zero term counts will be set to 1.0
hash algorithm to use
strategy to determine whether to use shared hash space for all included features
if true, include indices when hashing a feature that has them (OPLists or OPVectors)
max number of features (hashes)
number of features (hashes) to generate
number of inputs
if true, prepends a input feature name to each token of that feature
Hashing Parameters
if true, include indices when hashing a feature that has them (OPLists or OPVectors)
if true, prepends a input feature name to each token of that feature
number of features (hashes) to generate
number of inputs
max number of features (hashes)
if true, term frequency vector will be binary such that non-zero term counts will be set to 1.0
hash algorithm to use
strategy to determine whether to use shared hash space for all included features