cv_loop_train: iterates training a model with CV (serial version)
In skimlab/CCSBUtils: R Utilitiy Functions for CCSB
View source: R/classifier_train.R
cv_loop_train R Documentation
iterates training a model with CV (serial version)
Description
iterates training a model with CV (serial version)
Usage
cv_loop_train(
data,
cls,
stratify = NA,
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")
)
Arguments
data
input matrix, of dimension nobs x nvars; each row is an
observation vector. Since this is an input to glmnet, it
should be the format that can be used with glmnet
cls
class labels
K
...
resampling_rate
...
n_features
...
filter_method
...
filter_direction
...
filter_threshold_diff
...
filter_threshold_score
...
observation_weights
...
feature_weights
...
Value
a list of trained models – see cv_loop_train_iter
skimlab/CCSBUtils documentation built on March 30, 2022, 4:52 a.m.
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.
View source: R/classifier_train.R
| cv_loop_train | R Documentation |
iterates training a model with CV (serial version)
Description
iterates training a model with CV (serial version)
Usage
cv_loop_train(
data,
cls,
stratify = NA,
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")
)
Arguments
data |
input matrix, of dimension |
cls |
class labels |
K |
... |
resampling_rate |
... |
n_features |
... |
filter_method |
... |
filter_direction |
... |
filter_threshold_diff |
... |
filter_threshold_score |
... |
observation_weights |
... |
feature_weights |
... |
Value
a list of trained models – see cv_loop_train_iter
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.