Function reference • binaryPPIclassifier

All functions
`binnedcp.plot()`	Binned checker plot to display results from all-by-all screens
`confusion.matrix()`	Function to calculate a confusion matrix for
`example_ppi_prediction`	Example prediction
`learning.curve()`	Function to calculate and plot the accuracy, hinge loss and binary cross-entropy loss of a machine learning prediction using the ppi.prediction function.
`luthy_reference_sets`	LuTHy reference sets
`ppi.prediction()`	Function to use a support vector or random forest machine learning algorithm or to classify quantitative protein-protein interaction data.
`probDis.plot()`	Plot a scatter plot of the probability distribution against the primary assay feature
`probGrid.plot()`	Plot a probability grid from the mean probabilities from the 'ensembleSize' number of models
`recovery.plot()`	Plot a bar diagram of the recovery rates at 50%, 75% and 95% probability
`recovery.rate()`	Function to calculate the recovery rate from binary PPI assays.
`roc.plot()`	Plot ROC curve of the predicted probabilities against the assay features the ML was trained on

Reference