Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:t-SNE | perplexity |
| gptkb:Random_Forest_Ensemble | minimum samples per leaf |
| gptkb:lasso_regression | lambda (regularization parameter) |
| gptkb:Boosted_Trees | Learning Rate |
| gptkb:Support_Vector_Regression | epsilon |
| gptkb:Stochastic_gradient_descent | learning rate |
| gptkb:Stochastic_gradient_descent | batch size |
| gptkb:Skip-gram_model | learning rate |
| gptkb:Random_Forest | min samples split |
| gptkb:Lasso_Regression | Regularization strength (lambda) |
| gptkb:GradientBoostingRegressor | min_samples_leaf |
| gptkb:RMSprop | learning rate |
| gptkb:Soft_Actor-Critic_(SAC) | discount factor (gamma) |
| gptkb:Elastic_Net | l1_ratio |
| gptkb:Skip-gram_model | negative sampling |
| gptkb:GradientBoostingRegressor | subsample |
| gptkb:Multinomial_Naive_Bayes | fit_prior |
| gptkb:GradientBoostingRegressor | learning_rate |
| gptkb:Random_Forest | number of trees |