confusionMatrix.BigBang: Computes the class confusion matrix from a class prediction...

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Computes the class confusion matrix from a class prediction matrix.

Usage

## S3 method for class 'BigBang'
confusionMatrix(o, cm, ...)

Arguments

cm	The confusion matrix, If not specified classPredictionMatrix method is call using the BigBang object provided and ...
...	Further parameters passed to classPredictionMatrix when cm is not specified.

Details

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.

Value

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.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see BigBang. *classPredictionMatrix(), *confusionMatrix().

Examples

## 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)
 

galgo documentation built on May 2, 2019, 4:20 a.m.