Unlock instant, AI-driven research and patent intelligence for your innovation.

Data classification by kernel density shape interpolation of clusters

a clustering and data technology, applied in the field of data classification, can solve the problems of insufficient classification using proximity to either the centroids of clusters or support vectors, and achieve the effect of accurately identifying outlier data points

Active Publication Date: 2009-05-21
SAP AG
View PDF4 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In classification, a collection of labeled patterns is provided, and the problem is to label a newly encountered, yet unlabeled, pattern.
In the case of clustering, the problem is to group a given collection of unlabeled patterns into meaningful clusters.
Classification using proximity to either centroids of clusters or support vectors is generally inadequate to properly classify data points.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Data classification by kernel density shape interpolation of clusters
  • Data classification by kernel density shape interpolation of clusters
  • Data classification by kernel density shape interpolation of clusters

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024]While the specification concludes with claims defining the features of the invention that are regarded as novel, it is believed that the invention will be better understood from a consideration of the description of exemplary embodiments in conjunction with the drawings. It is of course to be understood that the embodiments described herein are merely exemplary of the invention, which can be embodied in various forms. Therefore, specific structural and functional details disclosed in relation to the exemplary embodiments described herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriate form. Further, the terms and phrases used herein are not intended to be limiting but rather to provide an understandable description of the invention.

[0025]Exemplary embodiments of the present invention described herein can be implemented to perform data classific...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A data processing system is provided that comprises a processor, a random access memory for storing data and programs for execution by the processor, and computer readable instructions stored in the random access memory for execution by the processor to perform a method for obtaining a shape interpolated representation of shapes of clusters in an image of a clustered dataset. The method comprises generating a density estimate value of each grid point of a set of grid points sampled from the image at a specified resolution for each cluster using a kernel density function; evaluating the density estimate value of each grid point for each cluster to identify a maximum density estimate value of each grid point and a cluster associated with the maximum density estimate value; and adding each grid point for which the maximum density estimate value exceeds a specified threshold to the associated cluster to form a shape interpolated representation.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]This application is a continuation of U.S. patent application Ser. No. 11 / 940,739, filed Nov. 15, 2007, the disclosure of which is incorporated by reference herein in its entirety.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]Exemplary embodiments of the present invention relate to data classification, and more particularly, to shape interpolation of clustered data.[0004]2. Description of Background[0005]Data mining involves sorting through large amounts of data and extracting relevant predictive information. Traditionally used by business intelligence organizations and financial analysts, data mining is increasingly being used in the sciences to extract information from the enormous datasets that are generated by modern experimental and observational methods. Data mining can be used to identify trends within data that go beyond simple analysis through the use of sophisticated algorithms.[0006]Many data mining application...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(United States)
IPC IPC(8): G06F17/30G06N20/10G06V10/764
CPCG06K9/6226G06N99/005G06K9/6273G06N20/00G06N20/10G06V10/764G06F18/2321G06F18/2414
Inventor SYEDA-MAHMOOD, TANVEERHAAS, PETER J.LAKE, JOHN M.LOHMAN, GUY M.
Owner SAP AG