Gradient-based optimization of hyperparameters for base-pairing profile local alignment kernels.

研究成果: Article査読

1 被引用数 (Scopus)

抄録

We have recently proposed novel kernel functions, called base-pairing profile local alignment (BPLA) kernels for discrimination and detection of functional RNA sequences using SVMs. We employ STRAL's scoring function which takes into account sequence similarities as well as upstream and downstream base-pairing probabilities, which enables us to model secondary structures of RNA sequences. In this paper, we develop a method for optimizing hyperparameters of BPLA kernels with respect to discrimination accuracy using a gradient-based optimization technique. Our experiments show that the proposed method can find a nearly optimal set of parameters much faster than the grid search on all parameter combinations.

本文言語English
ページ(範囲)128-138
ページ数11
ジャーナルGenome informatics. International Conference on Genome Informatics
23
1
DOI
出版ステータスPublished - 2009 10

ASJC Scopus subject areas

  • Medicine(all)

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