Methods for mapping data into lower dimensions

摘要

Methods and systems for creating ensembles of hypersurfaces in high-dimensional feature spaces, and to machines and systems relating thereto. More specifically, exemplary aspects of the invention relate to methods and systems for generating supervised hypersurfaces based on user domain expertise, machine learning techniques, or other supervised learning techniques. These supervised hypersurfaces may optionally be combined with unsupervised hypersurfaces derived from unsupervised learning techniques. Lower-dimensional subspaces may be determined by the methods and systems for creating ensembles of hypersurfaces in high-dimensional feature spaces. Data may then be projected onto the lower-dimensional subspaces for use, e.g., in further data discovery, visualization for display, or database access. Also provided are tools, systems, devices, and software implementing the methods, and computers embodying the methods and/or running the software, where the methods, software, and computers utilize various aspects of the present invention relating to analyzing data.

主权项

1. A method for analysis of a high-dimensional feature space comprising labelled data, comprising:
generating a first supervised hypersurface and a first vector normal to the first hypersurface using supervised learning techniques on said labelled data; generating a second unsupervised hypersurface and a second vector normal to the second hypersurface using unsupervised learning techniques on said labelled data after removing the labels; selecting a subspace comprising the supervised hypersurface and unsupervised hypersurface; projecting data from the high-dimensional feature space onto the orthonormal basis that spans the selected subspace comprising the first vector normal to the first hypersurface and the second vector normal to the second hypersurface; and outputting the projected data into a computer memory.