%feature("docstring") OT::MixtureClassifier "Particular classifier based on a mixture distribution. Available constructors: MixtureClassifier(*mixtDist*) Parameters ---------- mixtDist : :class:`~openturns.Mixture` A mixture distribution. See also -------- Classifier, ExpertMixture Notes ----- This implements a mixture classifier which is a particular classifier based on a mixture distribution: .. math:: p( \vect{x} ) = \sum_{i=1}^N w_i p_i ( \vect{x} ) The classifier proposes :math:`N` classes. The rule to assign a point :math:`\vect{x}` to a class :math:`i` is defined as follows: .. math:: i = \argmax_k \log w_k p_k( \vect{x} ) See useful methods :meth:`classify` and :meth:`grade`." // --------------------------------------------------------------------- %feature("docstring") OT::MixtureClassifier::classify "Classify points according to the classifier. **Available usages**: classify(*inputPoint*) classify(*inputSample*) Parameters ---------- inputPoint : sequence of float A point to classify. inputSample : 2-d a sequence of float A set of point to classify. Notes ----- The classifier proposes :math:`N` classes where :math:`N` is the dimension of the mixture distribution *mixtDist*. The rule to assign a point :math:`\vect{x}` to a class :math:`i` is defined as follows: .. math:: i = \argmax_k \log w_k p_k( \vect{x} ) In the first usage, it returns an integer which corresponds to the class where *inputPoint* has been assigned. In the second usage, it returns an :class:`~openturns.Indices` that collects the class of each point of *inputSample*." // --------------------------------------------------------------------- %feature("docstring") OT::MixtureClassifier::grade "Grade points according to the classifier. **Available usages**: grade(*inputPoint, k*) grade(*inputSample, classList*) Parameters ---------- inputPoint : sequence of float A point to grade. inputSample : 2-d a sequence of float A set of point to grade. k : integer The class number. classList : sequence of integer The list of class number. Notes ----- The grade of :math:`\vect{x}` with respect to the class *k* is :math:`log w_k p_k ( \vect{x} )`. In the first usage, it returns a real that grades *inputPoint* with respect to the class *k*. The greatest, the best. In the second usage, it returns an :class:`~openturns.Indices` that collects the grades of the :math:`i^{th}` point of *inputSample* with respect to the :math:`i^{th}` class of *classList*." // --------------------------------------------------------------------- %feature("docstring") OT::MixtureClassifier::getMixture "Accessor to the mixture distribution. Returns ------- mixtDist : :class:`~openturns.Mixture` The mixture distribution." // --------------------------------------------------------------------- %feature("docstring") OT::MixtureClassifier::setMixture "Accessor to the mixture distribution. Parameters ---------- mixtDist : :class:`~openturns.Mixture` The mixture distribution."