code: def __init__(
      self,
      n_components=None,
      init=None,
      solver="cd",
      beta_loss="frobenius",
      tol=1e-4,
      max_iter=200,
      random_state=None,
      alpha=0.0,
      l1_ratio=0.0,
      verbose=0,
      shuffle=False,
  ):
      self.n_components = n_components
      self.init = init
      self.solver = solver
      self.beta_loss = beta_loss
      self.tol = tol
      self.max_iter = max_iter
      self.random_state = random_state
      self.alpha = alpha
      self.l1_ratio = l1_ratio
      self.verbose = verbose
      self.shuffle = shuffle
  
imports: import re
  from pprint import PrettyPrinter
  import numpy
  from sklearn.utils._pprint import _EstimatorPrettyPrinter
  from sklearn.linear_model import LogisticRegressionCV
  from sklearn.pipeline import make_pipeline
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_selection import SelectKBest, chi2
  from sklearn import config_context
label_desc: Use image node_id 1 to create a new NMF object from inherited base classes: BaseEstimator with example: obj = NMF(n_components, init, solver, beta_loss, tol, max_iter, random_state, alpha, l1_ratio, verbose, shuffle)