[Rd] confusion() -- generic function in package mda -- generally useful?

Martin Maechler Martin Maechler <maechler@stat.math.ethz.ch>
Wed, 14 Nov 2001 16:59:08 +0100


For a private package ("soon" to be on CRAN),
I started looking at and thinking about the function confusion() from the
mda package and wondered if it wouldn't make sense to provide the generic
function in base R and also think about making the default for the `true'
argument equal to  fitted(object).

One could write methods for confusion() for almost all classifiers 
which would be a nice universal approach.
Also, the value (a confusion matrix contingency table with some "useful"
attributes) could be made a bit more explicit.

Good or not so good idea?  alternatives?

Martin Maechler <maechler@stat.math.ethz.ch>	http://stat.ethz.ch/~maechler/
Seminar fuer Statistik, ETH-Zentrum  LEO D10	Leonhardstr. 27
ETH (Federal Inst. Technology)	8092 Zurich	SWITZERLAND
phone: x-41-1-632-3408		fax: ...-1228			<><

>>   Confusion Matrices
>> 
>>   Description:
>> 
>>        Compute the confusion matrix between two factors, or for an fda or
>>        mda object.
>> 
>>   Usage:
>> 
>>        confusion(object, true, ...)
>>        confusion(object, data, ...)
>> 
>>   Arguments:
>> 
>>     object: the predicted factor, or an fda or mda model object.
>> 
>>       true: the true factor.
>> 
>>       data: a data frame (list) containing the test data.
>> 
>>        ...: further arguments to be passed to or from methods.
>> 
>>   Details:
>> 
>>        This is a generic function.
>> 
>>   Value:
>> 
>>        For the default method essentially `table(object, true)', but with
>>        some useful attribute(s).
>> 
>>   See Also:
>> 
>>        `fda', `predict.fda'
>> 
>>   Examples:
>> 
>>        data(iris)
>>        irisfit <- fda(Species ~ ., data = iris)
>>        confusion(predict(irisfit, iris), iris$Species)
>>        ##            Setosa Versicolor Virginica 
>>        ##     Setosa     50          0         0
>>        ## Versicolor      0         48         1
>>        ##  Virginica      0          2        49
>>        ## attr(, "error"):
>>        ## [1] 0.02

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