class_docstr: return a logistic regression problem
  
  There is a dataset consisting of features (vectors of norm <=1)
  and labels (+1,-1), represented as a numpy array.
  There is also an L2 regularizer.
docstr: " computes the accuracy of the model gievn by w
code: def accuracy(self, param):
      """ " computes the accuracy of the model gievn by w"""
      score_pred = np.dot(self.input_vecs, param)
      label1_prob = np.where(
          score_pred >= 0,
          1 / (1 + np.exp(-score_pred)),
          np.exp(score_pred) / (1 + np.exp(score_pred)),
      )
      return np.mean(np.where(label1_prob >= 0.5, 1, -1) == self.labels)
  
file_path: privacy/research/dp_newton/src/my_logistic_regression.py
imports: import numpy
label_desc: Use image node_id 4 for calling the MyLogisticRegression obj's underlying member method code with example usage: obj.accuracy(param) and returns: np