FEATURE SELECTION ALGORITHM UNDER CONDITIONS OF NOISY DATA AND LIMITED RECORDING

• US 20170124485A1
• Filed: 12/14/2016
• Published: 05/04/2017
• Est. Priority Date: 06/30/2015
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Arunkumar, Saritha, Yang, Su
• Granted Patent: US 10,318,892 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/2115 by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06F 18/2148 characterised by the process organisation or structure, e.g. boosting cascade
• CPC Class Codes: G06F 18/241 relating to the classification model, e.g. parametric or non-parametric approaches
• CPC Class Codes: G06F 18/24137 Distances to cluster centroïds
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/047 Pattern matching networks; Rete networks

Abstract

Application of inter-class and intra-class filtering, based on aggregate point-to-point distances, to vector data for purposes of filtering the vector data for purposes of pattern recognition. In some embodiments: (i) the inter-class filtering is based on Euclidean distance, in all dimensions, between vector data points in vector space; and/or (ii) the intra-class filtering is based on a distance, in all dimensions, between vector data points in vector space.

Claims

1. A method comprising:

applying, by machine logic of the computer, an inter-class filtering to a set of vector data, wherein;

the set of vector data includes a plurality of vector values from each class of a plurality of classes, and

the inter-class filtering is based, at least in part, on an inter-class distance; and

applying, by machine logic of the computer, an intra-class filtering to the set of vector data, wherein the intra-class filtering is based, at least in part, on an intra-class distance.

2. The method of claim 1, wherein the inter-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values; and

at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes.

3. The method of claim 1, wherein the intra-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

at least some of the vector values in the plurality of vector values of the first class.

4. The method of claim 1, further comprising:

performing, by machine logic of the computer, a pattern recognition related action, wherein the pattern recognition related action is based, at least in part, on the inter-class filtering and the intra-class filtering.

5. The method of claim 4, wherein performing a pattern recognition related action includes:

assigning, by machine logic of the computer, a pattern to each class in the plurality of classes, wherein the pattern is based on;

the inter-class filtering or the intra-class filtering.

6. The method of claim 4, wherein performing a pattern recognition related action includes:

determining, by machine logic of the computer, a class to which an unknown vector value in the plurality of vector values belongs based, at least in part, on a previous pattern recognition related action.

7. The method of claim 1, wherein:

the inter-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values; and

(ii) at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes; and

the intra-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

(ii) at least some of the vector values in the plurality of vector values of the first class.

8. A computer program product comprising:

a computer readable storage medium having stored thereon;

first instructions executable by a device to cause the device to apply, by machine logic of the computer, an inter-class filtering to a set of vector data, wherein;

the set of vector data includes a plurality of vector values from each class of a plurality of classes, and

the inter-class filtering is based, at least in part, on an inter-class distance; and

second instructions executable by a device to cause the device to apply, by machine logic of the computer, an intra-class filtering to the set of vector data, wherein the intra-class filtering is based, at least in part, on an intra-class distance.

9. The computer program product of claim 8, wherein the inter-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values; and

at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes.

10. The computer program product of claim 8, wherein the intra-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

at least some of the vector values in the plurality of vector values of the first class.

11. The computer program product of claim 8, further comprising:

third instructions executable by a device to cause the device to perform, by machine logic of the computer, a pattern recognition related action, wherein the pattern recognition related action is based, at least in part, on the inter-class filtering and the intra-class filtering.

12. The computer program product of claim 11, wherein third instructions to perform a pattern recognition related action include:

fourth instructions executable by a device to cause the device to assign, by machine logic of the computer, a pattern to each class in the plurality of classes, wherein the pattern is based on;

the inter-class filtering or the intra-class filtering.

13. The computer program product of claim 11, wherein third instructions to perform a pattern recognition related action include:

fourth instructions executable by a device to cause the device to determine, by machine logic of the computer, a class to which an unknown vector value in the plurality of vector values belongs based, at least in part, on a previous pattern recognition related action.

14. The computer program product of claim 8, wherein:

the inter-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values; and

(ii) at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes; and

the intra-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

(ii) at least some of the vector values in the plurality of vector values of the first class.

15. A computer system comprising:

a processor set; and

a computer readable storage medium;

wherein;

the processor set is structured, located, connected, and/or programmed to execute instructions stored on the computer readable storage medium; and

the instructions include;

first instructions executable by a device to cause the device to apply, by machine logic of the computer, an inter-class filtering to a set of vector data, wherein;

the set of vector data includes a plurality of vector values from each class of a plurality of classes, and

the inter-class filtering is based, at least in part, on an inter-class distance; and

second instructions executable by a device to cause the device to apply, by machine logic of the computer, an intra-class filtering to the set of vector data, wherein the intra-class filtering is based, at least in part, on an intra-class distance.

16. The computer system of claim 15, wherein the inter-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values; and

at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes.

17. The computer system of claim 15, wherein the intra-class distance is based on a sum of distances between:

a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

at least some of the vector values in the plurality of vector values of the first class.

18. The computer system of claim 15, further comprising:

third instructions executable by a device to cause the device to perform, by machine logic of the computer, a pattern recognition related action, wherein the pattern recognition related action is based, at least in part, on the inter-class filtering and the intra-class filtering.

19. The computer system of claim 18, wherein third instructions to perform a pattern recognition related action include:

fourth instructions executable by a device to cause the device to assign, by machine logic of the computer, a pattern to each class in the plurality of classes, wherein the pattern is based on;

the inter-class filtering or the intra-class filtering.

20. The computer system of claim 15, wherein:

the inter-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values; and

(ii) at least some of the vector values in the plurality of vector values of at least one other class of the plurality of classes; and

the intra-class distance is based on a sum of Euclidean distances between;

(i) a subject vector value in the plurality of vector values in a first class of the plurality of classes; and

(ii) at least some of the vector values in the plurality of vector values of the first class.