Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:Boosted_Trees | Subsample Ratio |
| gptkb:Skip-gram_model | negative sampling |
| gptkb:GradientBoostingRegressor | subsample |
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:Support_Vector_Regression | epsilon |
| gptkb:Boosted_Trees | Learning Rate |
| gptkb:Gradient_Boosted_Trees | Subsample Ratio |
| gptkb:k-NN | k (number of neighbors) |
| gptkb:Stochastic_gradient_descent | batch size |
| gptkb:Multinomial_Naive_Bayes | alpha |
| gptkb:Multinomial_Naive_Bayes | fit_prior |
| gptkb:LDA | alpha |
| gptkb:Support_Vector_Regression | C |
| gptkb:LDA | beta |
| gptkb:t-SNE | number of iterations |
| gptkb:Random_Forests | minimum samples per leaf |
| gptkb:Random_Forest | min samples split |
| gptkb:Soft_Actor-Critic_(SAC) | temperature parameter (alpha) |
| gptkb:Soft_Actor-Critic_(SAC) | discount factor (gamma) |
| gptkb:Elastic_Net_Regression | alpha |