class_docstr: The L2 (ridge) penalty applied to each parameter.
class_docstr_tok: ["The","L2","(","ridge",")","penalty","applied","to","each","parameter","."]
code: def __init__(self, weights=None):
      if weights is None:
          self.weights = 1.0
      else:
          self.weights = weights
  
imports: import numpy
label_desc: Use image node_id 1 to create a new L2Univariate object from inherited base classes: Penalty with example: obj = L2Univariate(weights)