select_hyper.ts_tune: Select Optimal Hyperparameters for Time Series Models
In daltoolbox: Leveraging Experiment Lines to Data Analytics
select_hyper.ts_tune R Documentation
Select Optimal Hyperparameters for Time Series Models
Description
Identifies the optimal hyperparameters by minimizing the error from a dataset of hyperparameters.
The function selects the hyperparameter configuration that results in the lowest average error.
It wraps the dplyr library.
Usage
## S3 method for class 'ts_tune'
select_hyper(obj, hyperparameters)
Arguments
obj
a ts_tune object containing the model and tuning settings
hyperparameters
hyperparameters dataset
Value
returns the optimized key number of hyperparameters
daltoolbox documentation built on Nov. 3, 2024, 9:06 a.m.
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| select_hyper.ts_tune | R Documentation |
Select Optimal Hyperparameters for Time Series Models
Description
Identifies the optimal hyperparameters by minimizing the error from a dataset of hyperparameters. The function selects the hyperparameter configuration that results in the lowest average error. It wraps the dplyr library.
Usage
## S3 method for class 'ts_tune'
select_hyper(obj, hyperparameters)
Arguments
obj |
a |
hyperparameters |
hyperparameters dataset |
Value
returns the optimized key number of hyperparameters
R Package Documentation
Browse R Packages
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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