validate {sboost} | R Documentation |
sboost Validation Function
Description
A k-fold cross validation algorithm for sboost.
Usage
validate(
features,
outcomes,
iterations = 1,
k_fold = 6,
positive = NULL,
verbose = FALSE
)
Arguments
features |
feature set data.frame. |
outcomes |
outcomes corresponding to the features. |
iterations |
number of boosts. |
k_fold |
number of cross-validation subsets. |
positive |
is the positive outcome to test for; if NULL, the first in alphabetical order will be chosen |
verbose |
If true, progress bars will be displayed in console. |
Value
An sboost_validation S3 object containing:
- performance
Final performance statistics for all stumps.
- training_summary_statistics
Mean and standard deviations for test statistics generated by
assess
cumulative statistics for each of the training sets.- testing_summary_statistics
Mean and standard deviations for test statistics generated by
assess
cumulative statistics for each of the testing sets.- training_statistics
sboost sboost_assessment cumulative statistics objects used to generate training_statistics.
- testing_statistics
sboost sboost_assessment cumulative statistics objects used to generate testing_statistics.
- classifier_list
sboost sboost_classifier objects created from training sets.
- outcomes
Shows which outcome was considered as positive and which negative.
- k_fold
number of testing and training sets used in the validation.
- call
Shows the parameters that were used for validation.
See Also
sboost
documentation.
Examples
# malware
validate(malware[-1], malware[1], iterations = 5, k_fold = 3, positive = 1)
# mushrooms
validate(mushrooms[-1], mushrooms[1], iterations = 5, k_fold = 3, positive = "p")