buildClassifier {cleanUpdTSeq} | R Documentation

## get 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,
                    genome=Drerio, alphabet=c("ACGT"))

### Arguments

`Ndata.NaiveBayes` | This is the negative training data, described further in `data.NaiveBayes`.
`Pdata.NaiveBayes` | This is the positive training data, described further in `data.NaiveBayes`.
`upstream` | This is the length of upstream sequence to use in the analysis.
`downstream` | This is the length of downstream sequence to use in the analysis.
`wordSize` | This is the size of the word to use as a feature for the upstream sequence. wordSize = 6 should always be used.
`genome` | Name of the genome to use to get sequence. To find out a list of available genomes, please type available.genomes() in R.
`alphabet` | These are the bases to use, for example DNA bases 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)
    }

[Package cleanUpdTSeq version 1.18.0 Index]