View source: R/04.buildClassifier.R
| buildClassifier | R Documentation | 
Computes the conditional a-posterior probabilities of a categorical class variable given independent predictor variables using the Bayes rule.
buildClassifier(
  Ndata.NaiveBayes,
  Pdata.NaiveBayes,
  upstream = 40L,
  downstream = 30L,
  wordSize = 6L,
  alphabet = c("ACGT")
)
| Ndata.NaiveBayes | A data.frame, containing features for the negative 
training data, described further in  | 
| Pdata.NaiveBayes | A data.frame, containing features for the positive 
training data, described further in  | 
| 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". | 
An object of class "naiveBayes".
Jianhong Ou
naiveBayes
if (interactive()){
    data(data.NaiveBayes)
    classifier <- buildClassifier(data.NaiveBayes$Negative, 
                                  data.NaiveBayes$Positive)
}
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