Geometrization for pattern recognition, data analysis, data merging, and multiple criteria decision making
OwnerAbel Wolmaninventor
Life of this patent
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Abstract
An analyzer/classifier/synthesizer/prioritizing tool for data comprises use of an admissible geometrization process with data transformed and partitioned by an input process into one or more input matrices and one or more partition classes and one or more scale groups. The data to be analyzed/classified/synthesized/prioritized is processed by an admissible geometrization technique such as 2-partition modified individual differences multidimensional scaling (2p-IDMDS) to produce at least a measure of geometric fit. Using the measure of geometric fit and possibly other 2p-IDMDS output, a back end process analyzes, synthesizes, classifies, and prioritizes data through patterns, structure, and relations within the data.
Claims22
A computer system for data scaling comprising:
- (a) a memory which is able to store data,
- (b) a processor which is operatively connected to the memory which will:
- (1) compute two partitions of the stored data, and
- (2) compute admissible geometrization on the two partitions of the stored data, and
- (3) compute admissibly transformed data so that said memory will store the transformed data, and
- (c) a display to display the transformed data to a user to interpret the stored transformed data as transformed data.
A method for quantitative aggregation of data comprising:
- (a) using a computer processor, receiving data;
- (b) forming two partitions of the received data;
- (c) applying admissible geometrization to the partitioned data to produce at least a plurality of deformation matrices;
- (d) computing sizes of the deformation matrices;
- and
- (e) interpreting the sizes of the deformation matrices as indicative of quantitative aggregation of the received data.
A computer system for quantitative aggregation of data comprising:
- (a) a memory which is able to store data,
- (b) a processor which is operatively connected to the memory which will:
- (1) compute two partitions of the stored data, and
- (2) compute admissible geometrization of the partitioned data, and
- (3) compute at least a plurality of deformation matrices, and
- (4) compute sizes of the plurality of deformation matrices so that said memory will store the sizes of the deformation matrices, and
- (c) a display to display the sizes of the deformation matrices to a user to use the stored sizes of the deformation matrices as indicative of quantitative aggregation of the received data.
A pattern recognition method comprising:
- (a) using a computer processor, receiving data;
- (b) forming two partitions of the received data;
- (c) applying admissible geometrization to the partitioned data to produce at least a plurality of deformation matrices;
- (d) analyzing the plurality of deformation matrices;
- and
- (e) using the analyzed deformation matrices for pattern recognition;
- wherein the deformation matrices comprise an output of the step of applying admissible geometrization to the partitioned data.
A computer system for pattern recognition comprising:
- (a) a memory which is able to store data,
- (b) a processor which is operatively connected to the memory which will:
- (1) compute two partitions of the stored data, and
- (2) compute admissible geometrization of the partitioned data, and
- (3) compute at least a plurality of deformation matrices, and
- (4) compute an analysis of the plurality of deformation matrices so that said memory will store the analysis of the deformation matrices, and
- (c) a display to display the analysis of the deformation matrices to a user to use the stored analysis of the deformation matrices for pattern recognition;
- wherein the deformation matrices comprise an output of the step of computing admissible geometrization of the partitioned data.
Dependencies are inferred from the claim text.