def build_model_rbm():
np.random.seed(12)
rbm_estimators = list()
# rbm = BernoulliRBM(random_state=12, verbose=0, n_components=in_dim)
rbm = BernoulliRBM(random_state=np.random.randint(1, 100), verbose=0)
lr = LogisticRegression()
rbm.learning_rate = 0.0001
# rbm.n_iter = 20
# rbm.n_components = 50
lr.C = 10.0
rbm_estimators.append(('rbm', rbm))
rbm_estimators.append(('lr', lr))
return rbm_estimators
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