Alternative names (1)
hasHyperparameterRandom triples
| Subject | Object |
|---|---|
| gptkb:Elastic_Net_Regression | alpha |
| gptkb:Random_Forests | minimum samples per leaf |
| gptkb:Elastic_Net | l1_ratio |
| gptkb:t-SNE | perplexity |
| gptkb:GradientBoostingRegressor | min_samples_split |
| gptkb:Support_Vector_Regression | epsilon |
| gptkb:lasso_regression | lambda (regularization parameter) |
| gptkb:t-SNE | learning rate |
| gptkb:Skip-gram_model | negative sampling |
| gptkb:GradientBoostingRegressor | max_features |
| gptkb:Soft_Actor-Critic_(SAC) | discount factor (gamma) |
| gptkb:Gradient_Boosted_Trees | Loss Function |
| gptkb:GradientBoostingRegressor | min_samples_leaf |
| gptkb:Random_Forest_Ensemble | maximum tree depth |
| gptkb:StochasticWeightAveraging | AveragingFrequency |
| gptkb:Skip-gram_model | window size |
| gptkb:LDA | number of topics |
| gptkb:Elastic_Net | alpha |
| gptkb:nu-SVR | nu |
| gptkb:Random_Forest | min samples split |