Title:
【発明の名称】多次元データの非線形マッピングのための方法、システムおよびコンピュータプログラム製品
Document Type and Number:
Japanese Patent JP2002543525
Kind Code:
A
Abstract:
A method, system and computer program product are provided for scaling, or dimensionally reducing, multi-dimensional data sets that scale well for large data sets. The invention scales multi-dimensional data sets by determining one or more non-linear functions between a sample of points from the multi-dimensional data set and a corresponding set of dimensionally reduced points. Thereafter, these one or more non-linear functions are used to non-linearly map additional points. The additional points may be members of the original multi-dimensional data set or may be new, previously unseen points. In an embodiment, the determination of the non-linear relationship between the sample of points from the multi-dimensional data set and the corresponding set of dimensionally reduced points is performed by a self-learning system such as a neural network. The additional points are mapped using the self-learning system in a feed-forward/predictive manner.
Inventors:
Agraphiotis, Dimitris Kay.
Lovanov, Victor S.
Salem, Francis Earl.
Lovanov, Victor S.
Salem, Francis Earl.
Application Number:
JP2000615919A
Publication Date:
December 17, 2002
Filing Date:
May 03, 2000
Export Citation:
Assignee:
3-Dimensional Pharmaceuticals, Incorporated
International Classes:
G06E1/00; G06E3/00; G06N3/02; G06F7/00; G06F15/18; G06F17/00; G06F17/17; G06G7/00; G06K9/62; G06N3/00; (IPC1-7): G06N3/02; G06N3/00
Attorney, Agent or Firm:
Shusaku Yamamoto