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 |