Summarize the results from an experiment object

Sumarizes the results of an experiment object of the type `obj$classifier` and `obj$crossval`. This is different from the digestMC(), which sumarizes a model collection obj$models

Usage

digest(
  obj,
  penalty = NULL,
  best.cv = TRUE,
  best.k = NULL,
  plot = FALSE,
  omit.na = TRUE
)

Arguments

obj:

The experiment object resulting from the learning process `fit()`

penalty:

A coefficient between 0 and 1, which is applied to penalize the performance of models as a consequence of model-size. We use this to select the best model of the population of models (default:NULL)

best.cv:

Should we chose the best model based on information learnerd cross validation (default:TRUE). This will work if the crossvalidation data is available. If not the best model will be selected with empirical results.

best.k:

If we do not wish to let the algorithm select the model size, we can fix this by setting the best.k with an integer indicating the number of variables in the model (default:NULL).

plot:

Should the digested results be plotted ? (default:FALSE)

omit.na:

Omit data with empty results (default:TRUE)

Value

an object with digested information such as the best models for each model-size, their respective scores, the best model.