Institute Homepage DE Sign In

Back

Empirical Inference Talk 2006

Graph boosting for molecular QSAR analysis

no image
Empirical Inference
Koji Tsuda
no image
Empirical Inference
Hiroto Saigo

We propose a new boosting method that systematically combines graph mining and mathematical programming-based machine learning. Informative and interpretable subgraph features are greedily found by a series of graph mining calls. Due to our mathematical programming formulation, subgraph features and pre-calculated real-valued features are seemlessly integrated. We tested our algorithm on a quantitative structure-activity relationship (QSAR) problem, which is basically a regression problem when given a set of chemical compounds. In benchmark experiments, the prediction accuracy of our method favorably compared with the best results reported on each dataset.

Author(s): Saigo, H. and Kadowaki, T. and Kudo, T. and Tsuda, K.
Year: 2006
Month: December
Day: 0
Bibtex Type: Talk (talk)
Digital: 0
Electronic Archiving: grant_archive
Event Name: NIPS 2006 Workshop on New Problems and Methods in Computational Biology
Event Place: Vancouver, BC, Canada
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@talk{5011,
  title = {Graph boosting for molecular QSAR analysis},
  abstract = {We propose a new boosting method that systematically combines graph mining and mathematical programming-based machine learning. Informative and interpretable subgraph features are greedily found by a series of graph mining calls. Due to our mathematical programming formulation, subgraph features and pre-calculated real-valued features are seemlessly integrated. We tested our algorithm on a quantitative structure-activity relationship (QSAR) problem, which is basically a regression problem when given a set of chemical compounds. In benchmark experiments, the prediction accuracy of our method favorably compared with the best results reported on each dataset.},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = dec,
  year = {2006},
  slug = {5011},
  author = {Saigo, H. and Kadowaki, T. and Kudo, T. and Tsuda, K.},
  month_numeric = {12}
}