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 # MOP training plan

 Last update: 16.07.2025 

Define the training plan for the models in a [MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...")'s competition. [More...](#details)

## <a name="nested-classes"></a>Classes

class [CreateSimpleTrainingPlan](class_create_simple_training_plan.xhtml) This class is used to create training plans for the [ScalarMOP](struct_scalar_m_o_p.xhtml "This is only a sketch of the possible ScalarMOPApproximate API Implementation shall be refined if mor...") competition. It sets up data according to an sample analysis to allow efficient training of the samples. It provides functions to access and cleanup the prepared data. [More...](class_create_simple_training_plan.xhtml#details)  
 struct [SimpleTrainingPlan](struct_simple_training_plan.xhtml) TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model A model is trained for a set of outputs. [More...](struct_simple_training_plan.xhtml#details)  
 struct [TrainingPlanBase](struct_training_plan_base.xhtml) TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model. [More...](struct_training_plan_base.xhtml#details)  
 ## <a name="typedef-members"></a>Typedefs

<a id="ga37a12bcf1472b71ce9c0c9718ddc0e60"></a>using **SubspaceMatrix** = std::vector&lt; ParameterImportanceVector &gt; <a id="ga6d456df98c9aac1f2df9281721d34b34"></a>using **SubspaceMatrixList** = std::vector&lt; SubspaceMatrix &gt; <a id="ga06ed57ab459b9357bd70cb8388ed3f91"></a>using **TrainingPlanCollection** = std::vector&lt; TrainingPlanVector &gt; <a id="ga1349d7ec6fd610ea4713a397b5956471"></a>using **TrainingPlanVector** = std::vector&lt; TrainingSetVector &gt; <a id="ga3cc6c187028a75738001438b0dfe46b4"></a>using **TrainingSetVector** = std::vector&lt; [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) &gt; ## <a name="enum-members"></a>Enumerations

<a id="gafce529ac7282fd94c419e8bea8492268"></a>enum [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) { **Training** = 0, **Test**, **Ignore**, **Undefined** } SampleTrainingUsage is a set of states, that a sample may be assigned to in a training plan.   
 ## <a name="var-members"></a>Variables

<a id="ga19c68a1522b497b227fd93ae875acc03"></a>nodefaultctor **QualityMeasureBase** <a id="details" name="details"></a>## Detailed Description

Define the training plan for the models in a [MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...")'s competition.