### Abstract

We consider the problem of discovering the optimal pattern from a set of strings and associated numeric attribute values. The goodness of a pattern is measured by the correlation between the number of occurrences of the pattern in each string, and the numeric attribute value assigned to the string. We present two algorithms based on suffix trees, that can find the optimal substring pattern in O(Nn) and O(N ^{2}) time, respectively, where n is the number of strings and N is their total length. We further present a general branch and bound strategy that can be used when considering more complex pattern classes. We also show that combining the O(N ^{2}) algorithm and the branch and bound heuristic increases the efficiency of the algorithm considerably.

Original language | English |
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Title of host publication | Discovery Science - 8th International Conference, DS 2005, Proceedings |

Pages | 44-56 |

Number of pages | 13 |

DOIs | |

Publication status | Published - Dec 1 2005 |

Event | 8th International Conference on Discovery Science, DS 2005 - , Singapore Duration: Oct 8 2005 → Oct 11 2005 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 3735 LNAI |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 8th International Conference on Discovery Science, DS 2005 |
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Country | Singapore |

Period | 10/8/05 → 10/11/05 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Discovery Science - 8th International Conference, DS 2005, Proceedings*(pp. 44-56). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3735 LNAI). https://doi.org/10.1007/11563983_6

**Practical algorithms for pattern based linear regression.** / Bannai, Hideo; Hatano, Kohei; Inenaga, Shunsuke; Takeda, Masayuki.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Discovery Science - 8th International Conference, DS 2005, Proceedings.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3735 LNAI, pp. 44-56, 8th International Conference on Discovery Science, DS 2005, Singapore, 10/8/05. https://doi.org/10.1007/11563983_6

}

TY - GEN

T1 - Practical algorithms for pattern based linear regression

AU - Bannai, Hideo

AU - Hatano, Kohei

AU - Inenaga, Shunsuke

AU - Takeda, Masayuki

PY - 2005/12/1

Y1 - 2005/12/1

N2 - We consider the problem of discovering the optimal pattern from a set of strings and associated numeric attribute values. The goodness of a pattern is measured by the correlation between the number of occurrences of the pattern in each string, and the numeric attribute value assigned to the string. We present two algorithms based on suffix trees, that can find the optimal substring pattern in O(Nn) and O(N 2) time, respectively, where n is the number of strings and N is their total length. We further present a general branch and bound strategy that can be used when considering more complex pattern classes. We also show that combining the O(N 2) algorithm and the branch and bound heuristic increases the efficiency of the algorithm considerably.

AB - We consider the problem of discovering the optimal pattern from a set of strings and associated numeric attribute values. The goodness of a pattern is measured by the correlation between the number of occurrences of the pattern in each string, and the numeric attribute value assigned to the string. We present two algorithms based on suffix trees, that can find the optimal substring pattern in O(Nn) and O(N 2) time, respectively, where n is the number of strings and N is their total length. We further present a general branch and bound strategy that can be used when considering more complex pattern classes. We also show that combining the O(N 2) algorithm and the branch and bound heuristic increases the efficiency of the algorithm considerably.

UR - http://www.scopus.com/inward/record.url?scp=33745322333&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745322333&partnerID=8YFLogxK

U2 - 10.1007/11563983_6

DO - 10.1007/11563983_6

M3 - Conference contribution

AN - SCOPUS:33745322333

SN - 3540292306

SN - 9783540292302

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 44

EP - 56

BT - Discovery Science - 8th International Conference, DS 2005, Proceedings

ER -