Description Usage Arguments Value Author(s) References
This function implements a simple Gaussian maximum likelihood discriminant rule, for diagonal class covariance matrices.
1 | stat.diag.da(ls, cll, ts, pool=1)
|
ls |
learning set data matrix, with rows corresponding to cases (i.e., mRNA samples) and columns to predictor variables (i.e., genes). |
cll |
class labels for learning set, must be consecutive integers. |
ts |
test set data matrix, with rows corresponding to cases and columns to predictor variables. |
pool |
logical flag. If |
List containing the following components
pred |
vector of class predictions for the test set. |
Sandrine Dudoit, sandrine@stat.berkeley.edu
Jane Fridlyand, janef@stat.berkeley.edu
S. Dudoit, J. Fridlyand, and T. P. Speed. Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data. June 2000. (Statistics, UC Berkeley, Tech Report \#576).
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