anova_filter | Univariate filters |
barplot_var_stability | Barplot variable stability |
bin_stat_filter | Univariate filter for binary classification with mixed predictor datatypes |
boot_anova | Bootstrap univariate filters |
boot_correl | Bootstrap univariate filters |
boot_filter | Bootstrap for filter functions |
boot_lm | Bootstrap univariate filters |
boot_ttest | Bootstrap univariate filters |
boot_wilcoxon | Bootstrap univariate filters |
boruta_filter | Boruta filter |
boxplot_expression | Boxplot expression levels of model predictors |
class_balance | Check class balance in training folds |
class_balance.default | Check class balance in training folds |
class_balance.nestcv.train | Check class balance in training folds |
class_stat_filter | Univariate filter for binary classification with mixed predictor datatypes |
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 |
correl_filter | Univariate filters |
cor_stat_filter | Univariate filter for binary classification with mixed predictor datatypes |
cva.glmnet | Cross-validation of alpha for glmnet |
cv_coef | Coefficients from outer CV glmnet models |
cv_varImp | Extract variable importance from outer CV caret models |
glmnet_coefs | glmnet coefficients |
glmnet_filter | glmnet filter |
innercv_preds | Inner CV predictions |
innercv_preds.nestcv.glmnet | Inner CV predictions |
innercv_preds.nestcv.train | 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 |
metrics | Model performance metrics |
model.hsstan | hsstan model for cross-validation |
nestcv.glmnet | Nested cross-validation with glmnet |
nestcv.SuperLearner | Outer cross-validation of SuperLearner model |
nestcv.train | Nested cross-validation for caret |
one_hot | One-hot encode |
outercv | Outer cross-validation of selected models |
outercv.default | Outer cross-validation of selected models |
outercv.formula | 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_stability | Plot variable stability |
pls_filter | Partial Least Squares filter |
prc | Build precision-recall curve |
prc.data.frame | Build precision-recall curve |
prc.default | Build precision-recall curve |
prc.nestcv.glmnet | Build precision-recall curve |
prc.nestcv.SuperLearner | Build precision-recall curve |
prc.nestcv.train | Build precision-recall curve |
prc.outercv | Build precision-recall curve |
prc.repeatcv | Build precision-recall curve |
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 |
predSummary | Summarise prediction performance metrics |
pred_nestcv_glmnet | Prediction wrappers to use fastshap with nestedcv |
pred_nestcv_glmnet_class1 | Prediction wrappers to use fastshap with nestedcv |
pred_nestcv_glmnet_class2 | Prediction wrappers to use fastshap with nestedcv |
pred_nestcv_glmnet_class3 | Prediction wrappers to use fastshap with nestedcv |
pred_SuperLearner | Prediction wrappers to use fastshap with nestedcv |
pred_train | Prediction wrappers to use fastshap with nestedcv |
pred_train_class1 | Prediction wrappers to use fastshap with nestedcv |
pred_train_class2 | Prediction wrappers to use fastshap with nestedcv |
pred_train_class3 | Prediction wrappers to use fastshap with nestedcv |
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 |
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 |
var_stability.nestcv.glmnet | Variable stability |
var_stability.nestcv.train | Variable stability |
weight | Calculate weights for class imbalance |
wilcoxon_filter | Univariate filters |