buildClassifier: Build a Naive Bayes Classifier

In haibol2016/cleanUpdTSeq: cleanUpdTSeq cleans up artifacts from polyadenylation sites from oligo(dT)-mediated 3' end RNA sequending data

Build a Naive Bayes Classifier

Description

Computes the conditional a-posterior probabilities of a categorical class variable given independent predictor variables using the Bayes rule.

Usage

buildClassifier(
  Ndata.NaiveBayes,
  Pdata.NaiveBayes,
  upstream = 40L,
  downstream = 30L,
  wordSize = 6L,
  alphabet = c("ACGT")
)

Arguments

Ndata.NaiveBayes	A data.frame, containing features for the negative training data, described further in data.NaiveBayes.
Pdata.NaiveBayes	A data.frame, containing features for the positive training data, described further in data.NaiveBayes.
upstream	An integer(1) vector, length of upstream sequence to retrieve.
downstream	An integer(1) vector, length of downstream sequence to retrieve.
wordSize	An integer(1) vector, size of the kmer feature for the upstream sequence. wordSize = 6 should always be used.
alphabet	A character(1) vector, a string containing DNA bases. By default, "ACTG".

Value

An object of class "naiveBayes".

Author(s)

Jianhong Ou

See Also

naiveBayes

Examples

if (interactive()){
    data(data.NaiveBayes)
    classifier <- buildClassifier(data.NaiveBayes$Negative, 
                                  data.NaiveBayes$Positive)
}

haibol2016/cleanUpdTSeq documentation built on April 14, 2022, 9:56 p.m.