Description Usage Arguments Value Author(s) See Also Examples

View source: R/buildClassifier.R

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

1 2 3 | ```
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

1 2 3 4 | ```
if (interactive()){
data(data.NaiveBayes)
classifier <- buildClassifier(data.NaiveBayes$Negative, data.NaiveBayes$Positive)
}
``` |

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