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Make predict_voting default value false in BoostAODE

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Ricardo Montañana Gómez 2024-03-12 00:26:28 +01:00
parent 8f3bb47cfd
commit 5db168d87b
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
2 changed files with 2 additions and 2 deletions
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2
bayesnet/ensembles/BoostAODE.h
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@ -7,7 +7,7 @@
namespace bayesnet { namespace bayesnet {
class BoostAODE : public Ensemble { class BoostAODE : public Ensemble {
public: public:
BoostAODE(bool predict_voting = true); BoostAODE(bool predict_voting = false);
virtual ~BoostAODE() = default; virtual ~BoostAODE() = default;
std::vector<std::string> graph(const std::string& title = "BoostAODE") const override; std::vector<std::string> graph(const std::string& title = "BoostAODE") const override;
void setHyperparameters(const nlohmann::json& hyperparameters) override; void setHyperparameters(const nlohmann::json& hyperparameters) override;

2
docs/BoostAODE.md
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@ -24,7 +24,7 @@ The hyperparameters defined in the algorithm are:
Default value is *-1* so every time any of those algorithms are called, the threshold has to be set to the desired value. Default value is *-1* so every time any of those algorithms are called, the threshold has to be set to the desired value.
- ***predict_voting*** (*boolean*): Sets whether the algorithm will use *model voting* to predict the result. If set to false, the weighted average of the probabilities of each model's prediction will be used. Default value: *true*. - ***predict_voting*** (*boolean*): Sets whether the algorithm will use *model voting* to predict the result. If set to false, the weighted average of the probabilities of each model's prediction will be used. Default value: *false*.
- ***predict_single*** (*boolean*): Sets whether the algorithm will use single-model prediction in the learning process. If set to *false*, all models trained up to that point will be used to calculate the prediction necessary to update the weights in the learning process. Default value: *true*. - ***predict_single*** (*boolean*): Sets whether the algorithm will use single-model prediction in the learning process. If set to *false*, all models trained up to that point will be used to calculate the prediction necessary to update the weights in the learning process. Default value: *true*.