Description Usage Arguments Value References See Also
Poisson distribution based custering based on PoiClaClu::Classify()
1 |
x |
A n-by-p training data matrix; n observations and p features. Used to train the classifier. |
centers |
c-by-p matrix returned by |
xte |
A m-by-p data matrix: m test observations and p features. The classifier fit on the training data set x will be tested on this data set. If NULL, then testing will be performed on the training set. |
... |
Arguments passed on to
|
ytehat |
The predicted class labels for each of the test observations (rows of xte). |
discriminant |
A m-by-K matrix, where K is the number of classes. The (i,k) element is large if the ith element of xte belongs to class k. |
ds |
A K-by-p matrix indicating the extent to which each feature is under- or over-expressed in each class. The (k,j) element is >1 if feature j is over-expressed in class k, and is <1 if feature j is under-expressed in class k. When rho is large then many of the elemtns of this matrix are shrunken towards 1 (no over- or under-expression). |
alpha |
Power transformation used (if transform=TRUE). |
D Witten (2011) Classification and clustering of sequencing data using a Poisson model. To appear in Annals of Applied Statistics.
PoiClaClu::Classify()
, find_centers()
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