evaluate_performance: Evaluate performance of a model in 'MLWIC2' on your dataset
In mikeyEcology/MLWIC2: Machine Learning for Wildlife Image Classification

evaluate_performance calculates some basic summary statistics of model performance using classify. After running classify, you will need to run make_output and have this output as your data frame to put into this function.

1	evaluate_performance(model_output, top5 = TRUE, label_tbl = speciesID)

`model_output`	The output of running `classify` after you have run `make_output` on this output.
`top5`	Boolean variable for if you want to evaluate top-5 results for the model. This will only work if you saved at least 5 guesses from the model in `classify` by specifying 'top_n=5' or greater.
`label_tbl`	A table with words to identify the classes in your dataset. If you are using the built in model, this is the speciesID data file that was downloaded with the package. If you are writing your own 'label_tbl', you need to have columns called "class_ID" and "group_name". For example, see head(speciesID)