ad | Constructor for "ad" class |
build_model | Build a model with feature selection and tuning |
center_scale | Center and scale data and remove predictors with near-zero... |
combine_sdf | Combine SDF files |
dwnld_mol | Download molecule structure |
dwnld_mol_list | Download multiple molecule structures |
eval_model | Evaluate a model using k-fold cross-validation |
eval_model_rep | Evaluate a model with replication |
find_col_outlier | Find outliers in a column of a data frame |
find_outlier | Find outliers in a vector |
Ka_to_delG | Ka to dG conversion |
make_extval | Make an external validation set |
make_regex | Convert to regex |
normalize_summary_stat | Find the best performing model in a list |
predict.ad | Find applicability domain |
predict.tune | Make predictions using the S3 "tune" object |
print.tune | Print an object of S3 class "tune" |
read_desc | Read a file of chemical descriptors |
read_desc_helper | Read a file of chemical descriptors (helper) |
read_desc_list | Read a list of chemical descriptor files |
remove_ad | Remove observations outside of the applicability domain |
remove_col_na | Remove columns based on proportion of NA values |
remove_col_outlier | Remove rows of a data frame based on column outliers |
remove_xoutlier | Remove X-outliers from data |
remove_zerovar | Remove predictors with near-zero variance |
replace_nan | Replace NaNs in a data frame with NA |
retain_name | Retain names in lapply |
sd_pop | Obtain standard deviation |
split_train | Create 'num' splits in training data saved in a single list |
train_svm | Output SVM model results over multiple folds |
train_svm_fold | A helper for 'train_svm'. |
tune | Tune parameters of a model-building method |
tune_helper | A helper function for 'tune' |
write_sdf | Write an SDF |
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