Computes the class confusion matrix from a class prediction matrix.
The confusion matrix, If not specified
Further parameters passed to
The matrix is computed getting the predicted class proportions for all samples; accumulating the proportions; finally producing propotions for all classes. This procedure is equivalent to having the same weights (priors) for all classes.
A matrix with original classes in rows and predicted classes in columns. Each value represent the “probability” for a sample within a given class to be predicted as any other class.
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
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## Not run: #bb is a BigBang object cpm <- classPredictionMatrix(bb) cpm cm <- confusionMatrix(bb) cm #equivalent and quicker because classPredictionMatrix is provided cm <- confusionMatrix(bb, cpm) cm specificityClass(bb, cm) specificityClass(bb, cpm) specificityClass(bb) # all are equivalent sensitivityClass(bb, cpm) sensitivityClass(bb, cm) sensitivityClass(bb) # all are equivalent ## End(Not run)
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