class_docstr: The L2 (ridge) penalty applied to each parameter.
class_docstr_tok: ["The","L2","(","ridge",")","penalty","applied","to","each","parameter","."]
code: def deriv2(self, params):
      return 2 * self.weights * np.ones(len(params))
  
imports: import numpy
label_desc: Use image node_id 4 for calling the L2Univariate obj's underlying member method code with example usage: obj.deriv2(params) and returns: unknown