Package index

Univariate Tests

Generate a table of univariate tests.

Utilities for evaluating (binary) classifier performance, including confusion matrix tools.

calc_confusion() print(<confusion_matrix>) summary(<confusion_matrix>) print(<summary_confusion_matrix>): Calculate confusion matrix
calc_brier(): Calculate the Brier Score
pull_stat(): Pull a Classification Performance Metric/Statistic
get_max_cutoff() get_spec_cutoff(): Get Distance Cutoffs
calc_auc() calc_emp_auc() calc_pepe_auc() calc_boot_auc(): Calculate Area Under Curve

Tools for creating and manipulating training data objects of class tr_data.

create_train() is.tr_data() plot(<tr_data>): Create a Training Data Object

Convenient wrappers for fitting various model types.

fit_gbm(): Fit a Generalized Boosted Regression Model
fit_kknn(): Fit Weighted k-Nearest Neighbor Classifier
fit_logistic(): Fit Multivariate Logistic Regression Model
fit_nb() print(<libml_nb>) predict(<libml_nb>) plot(<libml_nb>) plot(<naiveBayes>): Robustly Fit Naive Bayes Classifier
stripLMC(): Strip Linear Model Components

Predict, pull out components, manipulate, and interrogate model objects.

calc_predictions(<libml_nb>) calc_predictions(<naiveBayes>) calc_predictions(<randomForest>) calc_predictions(<gbm>) calc_predictions(<svm>) calc_predictions(<glm>) calc_predictions(<kknn>): Calculate Model Predictions
get_max_cutoff() get_spec_cutoff(): Get Distance Cutoffs
get_gini(): Calculate Sorted Gini Importance
get_model_coef(<glm>) get_model_coef(<lm>) get_model_coef(<lda>) get_model_coef(<libml_nb>) get_model_coef(<naiveBayes>) get_model_coef(<kknn>) get_model_coef(<randomForest>) get_model_coef(<gbm>) get_model_coef(<glmnet>) get_model_coef(<cv.glmnet>) get_model_coef(<train>) get_model_coef(<svm>): Get Coefficients of a Model
select_features(): Select Model Features
kfold_cv(): Calculate k-Fold Cross-Validation
reexports calc_predictions get_model_coef get_model_features: Objects exported from other packages

Plot various model fitting related visualizations.

Tools for generating and evaluating Reciever Operaterator Criterion.

calc_roc_fit(): Calculate ROC Curve Parameters
create_roc_data() filter_roc_data() calc_roc_perpendicular() calc_roc_corner(): Create ROC Data Table
geom_roc() geom_rocfit(): Plot a ROC Curve
plot_boot_roc(): Plot a ROC with CI95
plot_emp_roc(): Plot Empirical ROC Curve
roc_xy(): ROC Curve Coordinates
add_ss_box() calc_joint_CI95(): Add a Sensitivity/Specificity Box
calc_ci_binom(): Calculate Binomial Confidence Interval

Common parameter definitions used by the package.

Package data objects.