Budget maintenance strategy that merges two vectors. More...
#include <shark/Algorithms/Trainers/Budgeted/MergeBudgetMaintenanceStrategy.h>
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MergeBudgetMaintenanceStrategy () | |
constructor. More... | |
virtual void | addToModel (ModelType &model, InputType &alpha, ElementType &supportVector) |
std::string | name () const |
class name More... | |
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AbstractBudgetMaintenanceStrategy () | |
virtual void | addToModel (ModelType &model, InputType const &alpha, ElementType const &supportVector)=0 |
std::string | name () const |
return the class name More... | |
Additional Inherited Members | |
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typedef KernelExpansion< InputType > | ModelType |
typedef LabeledData< InputType, unsigned int > | DataType |
typedef DataType::element_type | ElementType |
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static void | findSmallestVector (ModelType const &model, size_t &minIndex, double &minAlpha) |
Budget maintenance strategy that merges two vectors.
\[ ||\alpha||_2\]
coefficient– only then a second one is searched for, by inspecting the expected weight degradation after merging. The vector with smallest weight degradation is the vector one should merge with the first one. By this heuristic, the merging strategy has complexity\[ \mathcal{O}(B) \]
. Compared with the projection strategy, merging should be faster, and stil obtains similar accuracy. Unluckily any kind of timing numbers are missing in the reference paper of Wang, Crammer and Vucetic.Definition at line 84 of file MergeBudgetMaintenanceStrategy.h.
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constructor.
Definition at line 93 of file MergeBudgetMaintenanceStrategy.h.
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inlinevirtual |
add to model. this is just a fake here, as it is unclear in general how to merge two objects, one needs to specialize this template.
[in,out] | model | the model the strategy will work with |
[in] | alpha | alphas for the new budget vector |
[in] | supportVector | the vector to add to the model by applying the maintenance strategy |
Definition at line 106 of file MergeBudgetMaintenanceStrategy.h.
References SHARKEXCEPTION.
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