summa-class: An S4 class to represent the summa output.
In learn-ensemble/R-SUMMA:

An S4 class to represent the summa output.

predictions: matrix of predictions
covariance_matrix: Square matrix of size learners containing covariance of learners
covariance_tensor: Cube tensor of size learners containing the covariance of three learners
weights: Contains weights for each method
nsamples: Number representing number of samples
nmethods: Number representing number of learners
majority_vote: A numeric vector of samples constructed by weighting each learner equally
summa: A numeric vector of samples constructed by weighting each learner by their estimated performance
type: A user defined character vector describing the data under analysis
actual_performance: A numeric vector of learnears representing actual performance of the learners, for binary data this is balanced accuracy for ranked data this is AUC
estimated_performance: A numeric vector of learners representing the summa estimated performance of learners
estimated_prevelance: A number corresponding to estimated prevelance
sampe_rank: A numeric vector ranking each sample by decreased confidence belonging to positive class using the summa ensemble