buildClassifier {cleanUpdTSeq} | 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, genome=Drerio, alphabet=c("ACGT"))
Ndata.NaiveBayes |
This is the negative training data, described further in |
Pdata.NaiveBayes |
This is the positive training data, described further in |
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. |
An object of class "naiveBayes".
Jianhong Ou
if (interactive()){ data(data.NaiveBayes) classifier <- buildClassifier(data.NaiveBayes$Negative, data.NaiveBayes$Positive) }