parameter
P12016
predicate
Indicates that one entity serves as a parameter or argument that configures, constrains, or influences the behavior or outcome of another entity or process.
Aliases (8)
- hyperparameter ×17
- parameterType ×15
- acceptsParameter ×11
- involvesParameter ×6
- configurableParameter ×5
- controlsParameter ×5
- interactionParameter ×1
- regularizationParameter ×1
Sample triples (112)
| Subject | Object |
|---|---|
| BRIN | autosummarize → |
| BRIN | autovacuum settings → |
| BRIN | pages_per_range → |
| Black–Scholes model | cumulative normal distribution function ("involvesParameter") → |
| Black–Scholes model | risk-free interest rate ("involvesParameter") → |
| Black–Scholes model | strike price ("involvesParameter") → |
| Black–Scholes model | time to maturity ("involvesParameter") → |
| Black–Scholes model | underlying asset price ("involvesParameter") → |
| Black–Scholes model | volatility of underlying asset ("involvesParameter") → |
| ColumnTransformer | force_int_remainder_cols:bool ("parameterType") → |
| ColumnTransformer | n_jobs:int or None ("parameterType") → |
| ColumnTransformer | remainder:str or estimator ("parameterType") → |
| ColumnTransformer | sparse_threshold:float ("parameterType") → |
| ColumnTransformer | transformer_weights:dict or None ("parameterType") → |
| ColumnTransformer | transformers:list of tuples ("parameterType") → |
| ColumnTransformer | verbose:bool ("parameterType") → |
| ColumnTransformer | verbose_feature_names_out:bool or str ("parameterType") → |
| Fourier's law of heat conduction | scalar thermal conductivity in isotropic media → |
| Fourier's law of heat conduction | thermal conductivity tensor → |
| Gaussian distribution | location parameter → |
| Gaussian distribution | mean → |
| Gaussian distribution | scale parameter → |
| Gaussian distribution | standard deviation → |
| Gaussian distribution | variance → |
| GridSearchCV | cv ("acceptsParameter") → |
| GridSearchCV | cv can be cross-validation splitter ("parameterType") → |
| GridSearchCV | cv can be int ("parameterType") → |
| GridSearchCV | error_score ("acceptsParameter") → |
| GridSearchCV | estimator ("acceptsParameter") → |
| GridSearchCV | iid ("acceptsParameter") → |
| GridSearchCV | n_jobs ("acceptsParameter") → |
| GridSearchCV | n_jobs can be -1 for using all processors ("parameterType") → |
| GridSearchCV | param_grid ("acceptsParameter") → |
| GridSearchCV | param_grid can be dict ("parameterType") → |
| GridSearchCV | param_grid can be list of dicts ("parameterType") → |
| GridSearchCV | pre_dispatch ("acceptsParameter") → |
| GridSearchCV | refit ("acceptsParameter") → |
| GridSearchCV | return_train_score ("acceptsParameter") → |
| GridSearchCV | scoring ("acceptsParameter") → |
| GridSearchCV | scoring can be callable ("parameterType") → |
| GridSearchCV | scoring can be string ("parameterType") → |
| GridSearchCV | verbose ("acceptsParameter") → |
| Ising model | J_{ij} ("interactionParameter") → |
| Ising model | inverse temperature β → |
| Lebesgue spaces | p → |
| LogisticRegression | C → |
| LogisticRegression | class_weight → |
| LogisticRegression | dual → |
| LogisticRegression | fit_intercept → |
| LogisticRegression | intercept_scaling → |
| LogisticRegression | l1_ratio → |
| LogisticRegression | max_iter → |
| LogisticRegression | multi_class → |
| LogisticRegression | n_jobs → |
| LogisticRegression | penalty → |
| LogisticRegression | random_state → |
| LogisticRegression | solver → |
| LogisticRegression | tol → |
| LogisticRegression | verbose → |
| LogisticRegression | warm_start → |
| Lorentz contraction | c (speed of light in vacuum) → |
| Lorentz contraction | v (relative velocity) → |
| PairGrid | aspect → |
| PairGrid | corner → |
| PairGrid | data → |
| PairGrid | despine → |
| PairGrid | dropna → |
| PairGrid | height → |
| PairGrid | hue → |
| PairGrid | hue_kws → |
| PairGrid | palette → |
| PairGrid | vars → |
| PairGrid | x_vars → |
| PairGrid | y_vars → |
| Prioritized Experience Replay DQN | alpha controls degree of prioritization ("hyperparameter") → |
| Prioritized Experience Replay DQN | beta controls strength of importance sampling correction ("hyperparameter") → |
| Riemann–Liouville integral | lower limit a → |
| Riemann–Liouville integral | order α → |
| SVC | C ("hyperparameter") → |
| SVC | C ("regularizationParameter") → |
| SVC | break_ties ("hyperparameter") → |
| SVC | cache_size ("hyperparameter") → |
| SVC | class_weight ("hyperparameter") → |
| SVC | coef0 ("hyperparameter") → |
| SVC | decision_function_shape ("hyperparameter") → |
| SVC | degree ("hyperparameter") → |
| SVC | gamma ("hyperparameter") → |
| SVC | kernel ("hyperparameter") → |
| SVC | max_iter ("hyperparameter") → |
| SVC | probability ("hyperparameter") → |
| SVC | random_state ("hyperparameter") → |
| SVC | shrinking ("hyperparameter") → |
| SVC | tol ("hyperparameter") → |
| SVC | verbose ("hyperparameter") → |
| Shockley diode equation | ideality factor n → |
| Shockley diode equation | saturation current I_s → |
| Shockley diode equation | thermal voltage V_T → |
| Wigner surmise | Dyson index β NERFINISHED → |
| Wigner surmise | level spacing s → |
| Zoom (macOS accessibility feature) | follow keyboard focus behavior ("configurableParameter") → |
| Zoom (macOS accessibility feature) | maximum zoom level ("configurableParameter") → |
| Zoom (macOS accessibility feature) | minimum zoom level ("configurableParameter") → |
| Zoom (macOS accessibility feature) | screen image smoothing ("configurableParameter") → |
| Zoom (macOS accessibility feature) | zoom style ("configurableParameter") → |
| black hole no-hair theorem | angular momentum → |
| black hole no-hair theorem | electric charge → |
| black hole no-hair theorem | mass → |
| function generator | DC offset ("controlsParameter") → |
| function generator | amplitude ("controlsParameter") → |
| function generator | duty cycle ("controlsParameter") → |
| function generator | frequency ("controlsParameter") → |
| function generator | phase (in some models) ("controlsParameter") → |