package bap-byteweight
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Byteweight algorithm interface.
Byteweight is a supervised machine learning algorithm. Based on the input string, where each substrings is labeled by true of false, a function is inferred that can map substrings into boolean domain.
For example, if the label function teaches whether the given substring is a start of a function, we can infer an algorithm for finding function starts.
include Bin_prot.Binable.S with type t := t
val bin_size_t : t Bin_prot.Size.sizerval bin_write_t : t Bin_prot.Write.writerval bin_read_t : t Bin_prot.Read.readerval __bin_read_t__ : (int -> t) Bin_prot.Read.readerval bin_writer_t : t Bin_prot.Type_class.writerval bin_reader_t : t Bin_prot.Type_class.readerval bin_t : t Bin_prot.Type_class.tval create : unit -> tcreate () creates an empty instance of the byteweigth decider.
train decider ~max_length test corpus train the decider on the specified corpus. The test function classifies extracted substrings. The max_length parameter binds the maximum length of substrings.
val length : t -> intlength decider total amount of different substrings known to a decider.
next t ~length ~threshold data begin the next positive chunk.
Returns an offset that is greater than begin of the next longest substring up to the given length, for which h1 / (h0 + h1) > threshold.
This is a specialization of the next_if function from the extended V1.V2.S interface.
val pp : Stdlib.Format.formatter -> t -> unitpp ppf decider prints all known to decider chunks.