View source: R/classifier_train.R
train_to_final_model | R Documentation |
A function that combines cv_loop_train and cv_train_final
train_to_final_model( data, cls, stratify = NA, train_final = TRUE, train_consensus = TRUE, fitControl, K = 25, resampling_rate = 0.8, n_features = NA, filter_method = c("ROC", "WILCOX"), filter_direction = c("two.sided", "greater", "less"), filter_threshold_diff = 1, filter_threshold_score = 0.8, observation_weights = NULL, feature_weights = c("uniform", "weighted"), predictor_score_threshold = 0.1, verbose = FALSE )
data |
input matrix, of dimension nobs x nvars; each row is an
observation vector. Since this is an input to |
cls |
class labels |
fitControl |
A list of training parameters. See
|
K |
... |
resampling_rate |
... |
n_features |
... |
filter_method |
... |
filter_direction |
... |
filter_threshold_diff |
... |
filter_threshold_score |
... |
observation_weights |
... |
feature_weights |
... |
predictor_score_threshold |
... |
a list of cv_loop_trained
(see
cv_loop_train_iter
), classification_results
(see
classification_summary_workflow
), and final_cv_model
(see cv_train_final
and additional slots)
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