NAME: CResult

SYNOPSIS: CResult [options] Net Input

DESCRIPTION

The CResult command is used to evaluate the performance of classification networks. A classification network has one output unit for each class in a classification problem. The "choice" or "guess" of the network for each input pattern is the class of the unit with the highest activity. If no -m option is specified, all output units of the network are considered class-units. The correct class for each pattern is defined as the class of the unit with the highest target (see the Streams section). The default output is percent patterns correct classified collapsed over all classes and separately for each class. By default, the streams of the network use 'Input' as the basename for data files (but see the -S option). It is convenient to name the output units by their respective class. The names of the units are used in the output of CResult.

OPTIONS

-S This option changes the interpretation of the argument "Input". With the -S option specified, the test data is taken from external files with the basenames taken from the rows of the script file "Input". Otherwize "Input" is itself a basename. In any case, the streams of the network read/write data from files specified by the basename together with the information about file extension and directory in each stream (see the Streams section).
-m object Mark an object. By default all output units are used as class-units. This options let you select a subset for of the units by specifying particular units or groups of units. There can be any number of -m options on the command line.
-c Print a confusion matrix.
-n N Print "within-top-N" statistics. This means that not only the patterns where the correct class was ranked higest by the network are counted, but also the patterns where the correct class was ranked as number two, three etc. 'N' determines the lowest ranking to count.
-x label Exclude frames were 'label' is the correct class.