validate | R Documentation |
A k-fold cross validation algorithm for sboost.
validate( features, outcomes, iterations = 1, k_fold = 6, positive = NULL, verbose = FALSE )
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. |
An sboost_validation S3 object containing:
Final performance statistics for all stumps.
Mean and standard deviations for test statistics
generated by assess
cumulative statistics for each of the training sets.
Mean and standard deviations for test statistics
generated by assess
cumulative statistics for each of the testing sets.
sboost sboost_assessment cumulative statistics objects used to generate training_statistics.
sboost sboost_assessment cumulative statistics objects used to generate testing_statistics.
sboost sboost_classifier objects created from training sets.
Shows which outcome was considered as positive and which negative.
number of testing and training sets used in the validation.
Shows the parameters that were used for validation.
sboost
documentation.
# 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")
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