# skcriteria.preprocessing.invert_objectives module¶

Implementation of functionalities for convert minimization criteria into maximization ones.

class skcriteria.preprocessing.invert_objectives.SKCObjectivesInverterABC[source]

Abstract class capable of invert objectives.

This abstract class require to redefine _invert, instead of _transform_data.

class skcriteria.preprocessing.invert_objectives.NegateMinimize[source]

Transform all minimization criteria into maximization ones.

The transformations are made by calculating the inverse value of the minimization criteria. $$\min{C} \equiv \max{-{C}}$$.

class skcriteria.preprocessing.invert_objectives.InvertMinimize[source]

Transform all minimization criteria into maximization ones.

The transformations are made by calculating the inverse value of the minimization criteria. $$\min{C} \equiv \max{\frac{1}{C}}$$

Notes

All the dtypes of the decision matrix are preserved except the inverted ones thar are converted to numpy.float64.

class skcriteria.preprocessing.invert_objectives.MinimizeToMaximize(*args, **kwargs)[source]

Bases: InvertMinimize

Transform all minimization criteria into maximization ones.

The transformations are made by calculating the inverse value of the minimization criteria. $$\min{C} \equiv \max{\frac{1}{C}}$$

Deprecated since version 0.7: Use skcriteria.preprocessing.invert_objectives.InvertMinimize instead

Notes

All the dtypes of the decision matrix are preserved except the inverted ones thar are converted to numpy.float64.