from sklearn.decomposition import NMF as _NMF
from base import BaseAlgo, TransformerMixin
from codec import codecs_manager
from util.param_util import convert_params
class NMF(TransformerMixin, BaseAlgo):
def __init__(self, options):
self.handle_options(options)
out_params = convert_params(
options.get('params', {}),
floats=['beta_loss','tol','alpha','l1_ratio'],
strs=['init','solver'],
ints=['k','max_iter','random_state'],
bools=['versbose','shuffle'],
aliases={'k': 'n_components'}
)
self.estimator = _NMF(**out_params)
def rename_output(self, default_names, new_names):
if new_names is None:
new_names = 'NMF'
output_names = ['{}_{}'.format(new_names, i+1) for i in xrange(len(default_names))]
return output_names
@staticmethod
def register_codecs():
from codec.codecs import SimpleObjectCodec
codecs_manager.add_codec('algos_contrib.NMF', 'NMF', SimpleObjectCodec)
codecs_manager.add_codec('sklearn.decomposition.nmf', 'NMF', SimpleObjectCodec)
