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The kappa statistic, along with user and producer error rates are conventionally used in the remote sensing to describe the effectiveness of ground cover classifications. Since it simultaneously considers both errors of commission and omission, kappa can be considered a more conservative measure of classification accuracy than the percentage of correctly classified items.
Kappa(class1, reference)Returns a list with 4 items
The percentage of correctly classified items.
The user accuracy for each category of the classification.
The producer accuracy for each category of the classification.
The kappa statistic.
A two way contingency table comparing the user supplied classification to the reference classification.
A vector describing a classification of experimental units.
A vector describing the "correct" classification of the experimental units in class1
Ken Aho
Jensen, J. R. (1996) Introductory digital imagery processing 2nd edition. Prentice-Hall.
reference<-c("hi","low","low","hi","low","med","med")
class1<-c("hi","hi","low","hi","med","med","med")
Kappa(class1,reference)
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