R: Predicting Categorical and Continuous Outcomes Using One in Ten Rule

# Predicting Categorical and Continuous Outcomes Using One in Ten Rule

## Documentation for package ‘CARRoT’ version 3.0.2

- DESCRIPTION file

## Help Pages

AUC | Area Under the Curve
av_out | Averaging out the predictive power
comb | Combining in a list
compute_max_length | Maximum number of the regressions
compute_max_weight | Maximum feasible weight of the predictors
compute_weights | Weights of predictors
cross_val | Cross-validation run
cub | Three-way interactions and squares
find_int | Finding the interacting terms based on the index
find_sub | Finds certain subsets of predictors
get_indices | Best regression
get_predictions | Predictions for multinomial regression
get_predictions_lin | Predictions for linear regression
get_probabilities | Probabilities for multinomial regression
make_numeric | Turning a non-numeric variable into a numeric one
make_numeric_sets | Transforming the set of predictors into a numeric set
quadr | Pairwise interactions and squares
regr_ind | Indices of the best regressions
sum_weights_sub | Cumulative weights of the predictors' subsets