We have developed a machine discovery system BONSAI which receives positive and negative examples as inputs and produces as a hypothesis a pair of a decision tree over regular patterns and an alphabet indexing. This system has succeeded in discovering reasonable knowledge on transmembrane domain sequences and signal peptide sequences by computer experiments. However, when several kinds of sequences are mixed in the data, it does not seem reasonable for a single BONSAI system to find a hypothesis of a reasonably small size with high accuracy. For this purpose, we have designed a system BONSAI Garden, in which several BONSAI's and a program called Gardener run over a network in parallel, to partition the data into some number of classes together with hypotheses explaining these classes accurately.
|Number of pages||8|
|Journal||Proceedings / ... International Conference on Intelligent Systems for Molecular Biology ; ISMB. International Conference on Intelligent Systems for Molecular Biology|
|Publication status||Published - 1995|
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