f7ed8f1b43044d87a3f527b75e1ad9e9e6cb2894,methods/shogun/linear_regression.py,SHOGUN_LINEARREGRESSION,metric,#SHOGUN_LINEARREGRESSION#,41

Before Change

    metric["runtime"] = totalTimer.ElapsedTime()

    if len(self.data) == 3:
      confusionMatrix = Metrics.ConfusionMatrix(self.data[2], predictions)
      metric["ACC"] = Metrics.AverageAccuracy(confusionMatrix)
      metric["MCC"] = Metrics.MCCMultiClass(confusionMatrix)
      metric["Precision"] = Metrics.AvgPrecision(confusionMatrix)

After Change

      elif self.solver == "cplex":
        model.set_solver_type(ST_CPLEX)

      elif self.solver == "glpk":
        model.set_solver_type(ST_GLPK)

      elif self.solver == "newton":
        model.set_solver_type(ST_NEWTON)

      elif self.solver == "direct":
        model.set_solver_type(ST_DIRECT)

      elif self.solver == "elasticnet":
        model.set_solver_type(ST_ELASTICNET)

      elif self.solver == "block_norm":
        model.set_solver_type(ST_BLOCK_NORM)

      else:
        raise ValueError("Provided solver not supported by current benchmark")

      model.train()

      if len(self.data) >= 2:

Instances