class_docstr: Implementation of the SoftImpute algorithm from:
  "Spectral Regularization Algorithms for Learning Large Incomplete Matrices"
  by Mazumder, Hastie, and Tibshirani.
class_docstr_tok: ["Implementation","of","the","SoftImpute","algorithm","from",":","''","Spectral","Regularization","Algorithms","for","Learning","Large","Incomplete","Matrices","''","by","Mazumder",",","Hastie",",","and","Tibshirani","."]
code: def _max_singular_value(self, X_filled):
      # quick decomposition of X_filled into rank-1 SVD
      _, s, _ = randomized_svd(X_filled, 1, n_iter=5, random_state=None)
      return s[0]
  
file_path: fancyimpute/fancyimpute/soft_impute.py
imports: import numpy
  from sklearn.utils.extmath import randomized_svd
  from sklearn.utils import check_array
  from .common import masked_mae
  from .solver import Solver
label_desc: Use image node_id 4 for calling the SoftImpute obj's underlying member method code with example usage: obj._max_singular_value(X_filled) and returns: s