barplot_var_stability   Barplot variable stability
boot_filter             Bootstrap for filter functions
boot_ttest              Bootstrap univariate filters
boruta_filter           Boruta filter
boxplot_expression      Boxplot expression levels of model predictors
class_balance           Check class balance in training folds
coef.cva.glmnet         Extract coefficients from a cva.glmnet object
coef.nestcv.glmnet      Extract coefficients from nestcv.glmnet object
collinear               Filter to reduce collinearity in predictors
combo_filter            Combo filter
correls2                Correlation between a vector and a matrix
cv_coef                 Coefficients from outer CV glmnet models
cv_varImp               Extract variable importance from outer CV caret
                        models
cva.glmnet              Cross-validation of alpha for glmnet
glmnet_coefs            glmnet coefficients
glmnet_filter           glmnet filter
innercv_preds           Inner CV predictions
innercv_roc             Build ROC curve from left-out folds from inner
                        CV
innercv_summary         Summarise performance on inner CV test folds
lines.prc               Add precision-recall curve to a plot
lm_filter               Linear model filter
mcc                     Matthews correlation coefficient
metrics                 Model performance metrics
model.hsstan            hsstan model for cross-validation
nestcv.SuperLearner     Outer cross-validation of SuperLearner model
nestcv.glmnet           Nested cross-validation with glmnet
nestcv.train            Nested cross-validation for caret
one_hot                 One-hot encode
outercv                 Outer cross-validation of selected models
plot.cva.glmnet         Plot lambda across range of alphas
plot.prc                Plot precision-recall curve
plot_alphas             Plot cross-validated glmnet alpha
plot_caret              Plot caret tuning
plot_lambdas            Plot cross-validated glmnet lambdas across
                        outer folds
plot_shap_bar           SHAP importance bar plot
plot_shap_beeswarm      SHAP importance beeswarm plot
plot_varImp             Variable importance plot
plot_var_ranks          Plot variable importance rankings
plot_var_stability      Plot variable stability
pls_filter              Partial Least Squares filter
prc                     Build precision-recall curve
predSummary             Summarise prediction performance metrics
pred_nestcv_glmnet      Prediction wrappers to use fastshap with
                        nestedcv
predict.cva.glmnet      Predict method for cva.glmnet models
predict.hsstan          Predict from hsstan model fitted within
                        cross-validation
predict.nestcv.glmnet   Predict method for nestcv.glmnet fits
randomsample            Oversampling and undersampling
ranger_filter           Random forest ranger filter
relieff_filter          ReliefF filter
repeatcv                Repeated nested CV
repeatfolds             Create folds for repeated nested CV
rf_filter               Random forest filter
slim                    Slim nestedcv models
smote                   SMOTE
stat_filter             Univariate filter for binary classification
                        with mixed predictor datatypes
summary_vars            Summarise variables
supervisedPCA           Supervised PCA plot
train_preds             Outer training fold predictions
train_roc               Build ROC curve from outer CV training folds
train_summary           Summarise performance on outer training folds
ttest_filter            Univariate filters
txtProgressBar2         Text Progress Bar 2
var_direction           Variable directionality
var_stability           Variable stability
weight                  Calculate weights for class imbalance
