Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures

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Documentation for package ‘xplus’ version 1.0.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

assess	Assess predictive performance
assess.xplus	Assess predictive performance
auc	Compute area under the ROC curve
auc_matrix	Compute AUC from matrix labels
binexample	Example binary labels dataset
coef.xplus	Extract coefficients from an xplus model
cutoff_example	Example cutoff values
fit_xplus_example	Example fitted xplus object
get_auc	Compute AUC for predictions from a model
get_auc.xplus	Compute AUC for predictions from a model
get_predictions	Build a tidy prediction table
lacs	LACS dataset
lacsSample	LACS sample dataset
predict.xplus	Predict from an xplus model
predicted_coefficients_example	Example predicted coefficients
predicted_y_example	Example predicted probabilities
print.summary.xplus	Print method for summary.xplus objects
print.xplus	Print an xplus model
summary.xplus	Summarize an xplus model
xplus	Fit an xplus model
xplus_object_example	Example xplus object