Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:LDA | number of topics |
| gptkb:Support_Vector_Regression | gptkb:operating_system |
| gptkb:Random_Forest | max depth |
| gptkb:Boosted_Trees | Tree Depth |
| gptkb:StochasticWeightAveraging | AveragingStartEpoch |
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:RMSprop | decay rate |
| gptkb:Lasso_Regression | Regularization strength (lambda) |
| gptkb:t-SNE | learning rate |
| gptkb:StochasticWeightAveraging | AveragingFrequency |
| gptkb:Soft_Actor-Critic_(SAC) | target smoothing coefficient (tau) |
| gptkb:GradientBoostingRegressor | max_features |
| gptkb:Multinomial_Naive_Bayes | alpha |
| gptkb:Random_Forest_Ensemble | maximum tree depth |
| gptkb:Soft_Actor-Critic_(SAC) | learning rate |
| gptkb:Gradient_Boosted_Trees | Subsample Ratio |
| gptkb:GradientBoostingRegressor | max_depth |
| gptkb:GradientBoostingRegressor | learning_rate |
| gptkb:nu-SVR | epsilon |
| gptkb:t-SNE | number of iterations |