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UFJF - Machine Learning Toolkit
0.51.8
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Namespace for ensemble methods. More...
#include <Ensemble.hpp>


Public Member Functions | |
| Ensemble (DataPointer< T > samples) | |
| Solution | getSolution () const |
| getSolution Returns the solution of the Ensemble method. More... | |
| Solution * | getSolutionRef () |
| getSolution Returns a reference to the solution of the Ensemble method. More... | |
| void | setLearner (Learner< T > *learner) |
| setLearner Set the base learner to be used by the ensemble method. Make sure to set the base learner parameters before setting it. More... | |
| void | setSamples (DataPointer< T > samples) override |
| setSamples Set the samples used by the Learner. More... | |
| void | setCommitteeSize (size_t c_size) |
| setCommitteeSize Set the learner committee size. More... | |
| size_t | size () |
| auto | begin () |
| auto | end () |
| LearnerPointer< T > | operator[] (size_t idx) const |
| auto | learners () |
Public Member Functions inherited from mltk::Learner< T > | |
| Learner (DataPointer< T > _samples) | |
| Learner (const Learner< T > &learner) | |
| virtual bool | train ()=0 |
| Function that execute the training phase of a Learner. More... | |
| virtual double | evaluate (const Point< T > &p, bool raw_value=false)=0 |
| Returns the class of a feature point based on the trained Learner. More... | |
| virtual mltk::Point< double > | batchEvaluate (const Data< T > &data) |
| evaluate a batch of points. More... | |
| virtual std::string | getFormulationString ()=0 |
| getFormulationString Returns a string that represents the formulation of the learner (Primal or Dual). More... | |
| auto | getSamples () |
| Get the Data used by the learner. More... | |
| double | getElapsedTime () const |
| Get the elapsed time in the training phase of the Learner. More... | |
| int | getCtot () const |
| Get the total number of updates of the Learner. More... | |
| int | getSteps () const |
| getSteps Returns the number of steps through the data by the Learner. More... | |
| int | getUpdates () const |
| getUpdates Returns the number of updates needed to get to the the solution. More... | |
| double | getMaxTime () const |
| getMaxTime Returns the maximum running time in the training phase of the Learner. More... | |
| double | getPredictionProbability () const |
| Get the probability of the last prediction. More... | |
| void | setSeed (const size_t _seed) |
| Set the seed to be used by the learner. More... | |
| virtual void | setSamples (const Data< T > &data) |
| setSamples Set the samples used by the Learner. More... | |
| void | setTimer (Timer _timer) |
| setTimer Set the timer used by the Learner. More... | |
| void | setSteps (int _steps) |
| Set the partial number of steps used in the training phase of the Learner. More... | |
| void | setCtot (int _ctot) |
| Set the partial number of updates of the Learner. More... | |
| void | setVerbose (int _verbose) |
| Set the level of verbose. More... | |
| void | setStartTime (double stime) |
| setStartTime Set the initial time of the Learner. More... | |
| void | setMaxTime (double maxtime) |
| Set the max time of execution. More... | |
| void | setEPS (double eps) |
| setEPS Set the precision of the Learner. More... | |
| void | setMaxIterations (int max_it) |
| setMaxIterations Set the max number of iterations of the Learner. More... | |
| void | setMaxEpochs (int MAX_EPOCHS) |
| Set the max number of epochs for the learner training. More... | |
| void | setMaxUpdates (int max_up) |
| setMaxIterations Set the max number of updates of the Learner. More... | |
| void | setLearningRate (double learning_rate) |
| Set the learning rate of the Learner. More... | |
Protected Attributes | |
| size_t | c_size {} |
| Committee size. More... | |
| std::vector< LearnerPointer< T > > | m_learners |
| Pointer to base learner used by the ensemble method. More... | |
| Solution | solution |
| Ensemble solution. More... | |
Protected Attributes inherited from mltk::Learner< T > | |
| std::shared_ptr< Data< T > > | samples |
| Samples used in the model training. More... | |
| double | rate |
| Learning rate. More... | |
| double | start_time |
| Initial time. More... | |
| double | max_time |
| Maximum time of training. More... | |
| int | steps |
| Number of steps in the data. More... | |
| int | ctot |
| Number of updates of the weights. More... | |
| double | EPS |
| Max precision. More... | |
| double | MIN_INC |
| Minimun Increment. More... | |
| int | MAX_IT |
| Max number of iterations. More... | |
| int | MAX_UP |
| Max number of updates. More... | |
| int | MAX_EPOCH |
| int | verbose |
| Verbose level of the output. More... | |
| Timer | timer |
| Timer used to measure the time elapsed in the execution of a Learner. More... | |
| size_t | seed |
| seed for random operations. More... | |
| double | pred_prob |
Namespace for ensemble methods.
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setCommitteeSize Set the learner committee size.
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setLearner Set the base learner to be used by the ensemble method. Make sure to set the base learner parameters before setting it.
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setSamples Set the samples used by the Learner.
| data | Samples to be used. |
Reimplemented from mltk::Learner< T >.
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Committee size.
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Pointer to base learner used by the ensemble method.
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Ensemble solution.