LudvigOlsen/cvms: cvms 1.1.0

In plot_confusion_matrix(), adds option to only have row and column percentages in the diagonal tiles. Thanks to @xgirouxb for the idea. Adds Process information to output with the settings used. Adds transparency. It has a custom print method, making it easy to read. Underneath it is a list, why all information is available using $ or similar. In most cases, the Family information has been moved into the Process object. Thanks to @daviddalpiaz for notifying me of the need for more transparency. In outputs, the Family information is (in most cases) moved into the new Process object. In binomial evaluate() and baseline(), Accuracy is now enabled by default. It is still disabled in cross_validate*() functions to guide users away from using it as the main criterion for model selection (as it is well known to many but can be quite bad in cases with imbalanced datasets.) Fixes: In binomial evaluation, the probabilities are now properly of the second class alphabetically. When the target column was a factor where the levels were not in alphabetical order, the second level in that order was used. The levels are now sorted before extraction. Thanks to @daviddalpiaz for finding the bug. Fixes: In grouped multinomial evaluation, when predictions are classes and there are different sets of classes per group, only the classes in the subset are used. Fixes: Bug in ROC direction parameter being set wrong when positive is numeric. In regression tests, the AUC scores were not impacted. Fixes: 2-class multinomial evaluation returns all expected metrics. In multinomial evaluation, the Class Level Results are sorted by the Class. Imports broom.mixed to allow tidying of coefficients from lme4::lmer models. Exports process_info_binomial(), process_info_multinomial(), process_info_gaussian() constructors to ensure the various methods are available. They are not necessarily intended for external use