Last data update: 2014.03.03

R: Construction of a classifier
createClassifierR Documentation

Construction of a classifier

Description

Creates a classifier for a training set.

Usage

createClassifier(trainingData, cross = FALSE)

Arguments

trainingData

A table, created by segmentImage with manually added classes.

cross

Does 10-fold cross validation to test the classifiers performance.

Details

Topological features include the density of cells and the size of the surrounding cytoplasma of a cell. These features depend on the size of the image. If training image and the image to classify have different size, these features can fool the classification and should not be enabled.

Value

A List containing:

classifier

The classifier

performance

cross validation performance

Author(s)

Henrik Failmezger, failmezger@mpipz.mpg.de

See Also

'createTrainingSet','classifyCells'

Examples

f = system.file("extdata", "trainingData.txt", package="CRImage")
#read training data
trainingData=read.table(f,header=TRUE)
#create classifier
classifier=createClassifier(trainingData)[[1]]

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(CRImage)
Loading required package: EBImage
Loading required package: DNAcopy
Loading required package: aCGH
Loading required package: cluster
Loading required package: survival
Loading required package: multtest
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, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, 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, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:EBImage':

    channel


Attaching package: 'aCGH'

The following object is masked from 'package:stats':

    heatmap

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/CRImage/createClassifier.Rd_%03d_medium.png", width=480, height=480)
> ### Name: createClassifier
> ### Title: Construction of a classifier
> ### Aliases: createClassifier
> ### Keywords: misc
> 
> ### ** Examples
> 
> f = system.file("extdata", "trainingData.txt", package="CRImage")
> #read training data
> trainingData=read.table(f,header=TRUE)
> #create classifier
> classifier=createClassifier(trainingData)[[1]]
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>