Accessors for the 'method' slot of an MLSeq object

Share:

Description

Used classification method for the trained model using classify function.

Usage

1
2
  ## S4 method for signature 'MLSeq'
method(object)

Arguments

object

an MLSeq object

Details

method slot stores the name of the classification method as "svm", support vector machines using radial-based kernel function; "bagsvm", support vector machines with bagging ensemble; "randomForest", random forest algorithm and "cart", classification and regression trees algorithm.

Author(s)

Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Izzet Parug Duru, Turgay Unver, Ahmet Ozturk

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
data(cervical)

data = cervical[c(1:150),]  # a subset of cervical data with first 150 features.

class = data.frame(condition=factor(rep(c("N","T"),c(29,29))))# defining sample classes.

n = ncol(data)  # number of samples
p = nrow(data)  # number of features

nTest = ceiling(n*0.2)  # number of samples for test set (20% test, 80% train).
ind = sample(n,nTest,FALSE)

# train set
data.train = data[,-ind]
data.train = as.matrix(data.train + 1)
classtr = data.frame(condition=class[-ind,])

# train set in S4 class
data.trainS4 = DESeqDataSetFromMatrix(countData = data.train,
colData = classtr, formula(~ condition))
data.trainS4 = DESeq(data.trainS4, fitType="local")

# Random Forest (RF) Classification
rf = classify(data = data.trainS4, method = "randomforest", normalize = "deseq", deseqTransform = "vst", cv = 5, rpt = 3, ref="T")

method(rf)