Description Usage Arguments Details Value Author(s) References Examples

This function performs a leave one out crossvalidation to estimate the
accuracy of a classifier built using `pdmClass`

.

1 | ```
pdmClass.cv(Y, X, method = c("pls", "pcr", "ridge"))
``` |

`Y` |
A vector of factors giving the class assignments for the samples to be used in the crossvalidation. |

`X` |
A matrix with samples in rows and observations in columns. Note that this is different than the usual paradigm for microarray data. |

`method` |
One of "pls", "pcr", "ridge", corresponding to partial least squares, principal components regression and ridge regression. |

This function performs a leave one out crossvalidation, which can be used to estimate the accuracy of a classifier. Each sample is removed in turn and a classifier is built using the remaining samples. The class of the removed sample is then predicted using the classifier. This is repeated for each sample, resulting in a vector of predicted class assignments for each sample in the original training set.

Although far from perfect, this method can be used to estimate the accuracy of a given classifier without splitting data into a training and testing set.

A vector of factors giving the predicted class assignments for each of
the samples in the training set. A confusion matrix can be constructed
using `confusion`

.

James W. MacDonald

http://www.sph.umich.edu/~ghoshd/COMPBIO/POPTSCORE

"Flexible Disriminant Analysis by Optimal Scoring" by Hastie, Tibshirani and Buja, 1994, JASA, 1255-1270.

"Penalized Discriminant Analysis" by Hastie, Buja and Tibshirani, Annals of Statistics, 1995 (in press).

1 2 3 4 5 6 |

```
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: fibroEset
Loading required package: mda
Loading required package: class
Loaded mda 0.4-10
Warning message:
*** Deprecation warning ***
The pdmclass package is deprecated and will be removed from
Bioconductor 3.6.
true
predicted b g h
b 11 0 5
g 0 12 0
h 0 0 18
```

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