Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:Random_Forests | maximum tree depth |
| gptkb:Soft_Actor-Critic_(SAC) | target smoothing coefficient (tau) |
| gptkb:Lasso_Regression | Regularization strength (lambda) |
| gptkb:Elastic_Net_Regression | alpha |
| gptkb:Soft_Actor-Critic_(SAC) | temperature parameter (alpha) |
| gptkb:GradientBoostingRegressor | loss |
| gptkb:Multinomial_Naive_Bayes | alpha |
| gptkb:GradientBoostingRegressor | n_estimators |
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:t-SNE | perplexity |
| gptkb:Random_Forests | number of trees |
| gptkb:Random_Forests | number of features per split |
| gptkb:t-SNE | number of iterations |
| gptkb:nu-SVR | gptkb:operating_system |
| gptkb:Random_Forest_Ensemble | maximum tree depth |
| gptkb:GradientBoostingRegressor | min_samples_leaf |
| gptkb:Random_Forests | minimum samples per leaf |
| gptkb:Skip-gram_model | embedding dimension |
| gptkb:Skip-gram_model | window size |
| gptkb:Soft_Actor-Critic_(SAC) | discount factor (gamma) |