<s> """<STR_LIT>""" <EOL> import numpy as np <EOL> from sklearn . pipeline import Pipeline <EOL> from sklearn . neural_network import BernoulliRBM <EOL> from sklearn . linear_model import LogisticRegression <EOL> from sklearn . naive_bayes import MultinomialNB <EOL> from sklearn . svm import SVC <EOL> from masque import datasets <EOL> from masque . transform import PatchTransformer <EOL> from masque . rbm import GaussianBernoulliRBM <EOL> from masque . playground . runners import plain_classify , pretrain_classify <EOL> rbm_svc = { <EOL> '<STR_LIT>' : BernoulliRBM ( n_components = <NUM_LIT> , verbose = True ) , <EOL> '<STR_LIT>' : SVC ( kernel = '<STR_LIT>' , verbose = True ) , <EOL> '<STR_LIT>' : lambda : datasets . cohn_kanade_shapes ( ) , <EOL> '<STR_LIT:data>' : lambda : datasets . cohn_kanade_shapes ( labeled_only = True ) , <EOL> } <EOL> dbn_svc = { <EOL> '<STR_LIT>' : Pipeline ( [ <EOL> ( '<STR_LIT>' , BernoulliRBM ( n_components = <NUM_LIT> , verbose = True ) ) , <EOL> ( '<STR_LIT>' , BernoulliRBM ( n_components = <NUM_LIT> , verbose = True ) ) , <EOL> ( '<STR_LIT>' , BernoulliRBM ( n_components = <NUM_LIT:32> , verbose = True ) ) , <EOL> ] ) , <EOL> '<STR_LIT>' : SVC ( kernel = '<STR_LIT>' , verbose = True ) , <EOL> '<STR_LIT>' : lambda : datasets . cohn_kanade_shapes ( ) , <EOL> '<STR_LIT:data>' : lambda : datasets . cohn_kanade_shapes ( labeled_only = True ) , <EOL> } </s>
