Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:RMSprop | epsilon |
| gptkb:Multinomial_Naive_Bayes | fit_prior |
| gptkb:GradientBoostingRegressor | min_samples_leaf |
| gptkb:Random_Forest | min samples split |
| gptkb:nu-SVR | nu |
| gptkb:nu-SVR | C |
| gptkb:Random_Forest_Ensemble | maximum tree depth |
| gptkb:Lasso_Regression | Regularization strength (lambda) |
| gptkb:LASSO | regularization parameter (lambda) |
| gptkb:Boosted_Trees | Subsample Ratio |
| gptkb:lasso_regression | lambda (regularization parameter) |
| gptkb:Random_Forests | number of trees |
| gptkb:RMSprop | learning rate |
| gptkb:Soft_Actor-Critic_(SAC) | learning rate |
| gptkb:Elastic_Net_Regression | l1_ratio |
| gptkb:Gradient_Boosted_Trees | Loss Function |
| gptkb:Support_Vector_Regression | gptkb:operating_system |
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:GradientBoostingRegressor | max_depth |
| gptkb:Stochastic_gradient_descent | batch size |