default_metalearner: Automatically Defined Metalearner
In jeremyrcoyle/sl3: Pipelines for Machine Learning and Super Learning
Description
Usage
Arguments
Details
View source: R/default_metalearner.R
Description
A sensible metalearner based on Lrnr_solnp is chosen based on
outcome type. This amounts to choosing an appropriate loss function and
combination function.
Usage
1
default_metalearner(outcome_type)
Arguments
outcome_type
a Variable_Type object
Details
Outcome Type Combination Function Loss Function
binomial metalearner_logistic_binomial loss_squared_error
categorical metalearner_linear_multinomial loss_loglik_multinomial
continuous metalearner_linear loss_squared_error
multivariate metalearner_linear_multivariate loss_squared_error_multivariate
jeremyrcoyle/sl3 documentation built on Feb. 3, 2022, 9:12 a.m.
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Description Usage Arguments Details
View source: R/default_metalearner.R
Description
A sensible metalearner based on Lrnr_solnp is chosen based on
outcome type. This amounts to choosing an appropriate loss function and
combination function.
Usage
1 | default_metalearner(outcome_type)
|
Arguments
outcome_type |
a Variable_Type object |
Details
| Outcome Type | Combination Function | Loss Function |
| binomial | metalearner_logistic_binomial | loss_squared_error |
| categorical | metalearner_linear_multinomial | loss_loglik_multinomial |
| continuous | metalearner_linear | loss_squared_error |
| multivariate | metalearner_linear_multivariate | loss_squared_error_multivariate |
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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