See Javadoc for complete documentation of this class.
Usage: <target> [-accept <Acceptance Tolerance>] [-window <Max Window Size>] [-cands <Max Number Candidates>]
Target: Desired value of class variable
Acceptance Tolerance: If the actual class variable is within this value of the target, consider the prediction a success
Maximum Window Size: Set this and Acceptance Tolerance to analyze accuracy as a function of tolerance window size
Max Number Candidates: Set this and acceptance tolerance in order to study accuracy as a function of number of candidates selected
These commands can be used to perform a variety of tasks, ranging from defining important settings about the object to actually using it.
evaluate $<dataset> – Evaluate measured vs. predicted class of entries
dataset: Dataset object to be evaluated.
These commands are run by calling "print <variable name> <command> [<options>]". Any output from that command will be printed to standard output.
baseline – Print statistics about the training data
rank – Prints how the performance of best-performing entries according to model predictions
roc – Print out Receiver Operating Characteristic curve
stats – Print out all statistics
window – Prints statistics regarding this model’s ability to act as a filter
Variables of this type can be saved in the following formats:
data – Save predicted and measured class values used to compute statistics