Feature selection algorithm under conditions of noisy data and limited recording

• US 10,318,892 B2
• Filed: 12/14/2016
• Issued: 06/11/2019
• Est. Priority Date: 06/30/2015
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Arunkumar, Saritha, Yang, Su
• Primary Examiner(s): Nakhjavan, Shervin K
• Application Number:
  US15/378,153
• Publication Number:
  US 20170124485A1
• Time in Patent Office: 909 Days
• Field of Search: None
• 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:

(I) generating a set of filtered vector data by;

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

the inter-class filtering reduces a number of vector values under consideration such that signal overlap is reduced between at least two classes of a plurality of classes,

each class of the plurality of classes respectively (i) represents a source for vector data and (ii) is associated with an entity or an object,

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

the inter-class filtering is based, at least in part, on an inter-class distance, wherein the inter-class distance is based on a sum of distances between;

a subject vector value, of a given class, 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; 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; and

(II) responsive to a determination that a pattern in the set of filtered vector data matches a pattern assigned to a given class, executing an action that is associated with the given class.

2. The method of claim 1, the method further comprising:

determining that the set of filtered vector data matches the pattern assigned to a given class based on a comparison of retained vectors for a plurality of classes to the pattern in the set of filtered vector data; and

selecting the action associated with the given class based on the matching, wherein the action associated with the given class includes one or more of;

(i) creating a new pattern recognition signature;

(ii) refining an existing pattern recognition signature;

(iii) discarding an ineffective pattern recognition signature;

(iv) assigning a given pattern to a given class based on a set of retained vectors; and

(v) performing additional pattern matching, and (vi) determining a class to which a given set of vectors belongs based on a previously performed action that is associated with the given class.

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 inter-class filtering reduces a number of vector values under consideration such that signal overlap is reduced between at least two classes of a plurality of classes,

each class of the plurality of classes respectively (i) represents a source for vector data and (ii) is associated with an entity or an object,

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

the inter-class filtering is based, at least in part, on an inter-class distance wherein the inter-class distance is based on a sum of distances between;

a subject vector value, of a given class, 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; 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; and

third instructions executable by a device to cause the device to respond to a determination that a pattern in the set of filtered vector data matches a pattern assigned to a given class by executing an action that is associated with the given class.

9. The computer program product of claim 8, wherein the further instructions further comprise instructions to:

determine that the set of filtered vector data matches the pattern assigned to a given class based on a comparison of retained vectors for a plurality of classes to the pattern in the set of filtered vector data; and

select the action associated with the given class based on the matching, wherein the action associated with the given class includes one or more of;

(i) creating a new pattern recognition signature;

(ii) refining an existing pattern recognition signature;

(iii) discarding an ineffective pattern recognition signature;

(iv) assigning a given pattern to a given class based on a set of retained vectors; and

(v) performing additional pattern matching, and (vi) determining a class to which a given set of vectors belongs based on a previously performed action that is associated with the given class.

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:

fourth 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:

fifth 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:

sixth 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 inter-class filtering reduces a number of vector values under consideration such that signal overlap is reduced between at least two classes of a plurality of classes,

each class of the plurality of classes respectively (i) represents a source for vector data and (ii) is associated with an entity or an object,

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

the inter-class filtering is based, at least in part, on an inter-class distance, wherein the inter-class distance is based on a sum of distances between;

 

a subject vector value, of a given class, 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; 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; and

third instructions executable by a device to cause the device to respond to a determination that a pattern in the set of filtered vector data matches a pattern assigned to a given class by executing an action that is associated with the given class.

16. The computer system of claim 15, wherein the further instructions further comprise instructions to:

determine that the set of filtered vector data matches the pattern assigned to a given class based on a comparison of retained vectors for a plurality of classes to the pattern in the set of filtered vector data; and

select the action associated with the given class based on the matching, wherein the action associated with the given class includes one or more of;

(i) creating a new pattern recognition signature;

(ii) refining an existing pattern recognition signature;

(iii) discarding an ineffective pattern recognition signature;

(iv) assigning a given pattern to a given class based on a set of retained vectors; and

(v) performing additional pattern matching, and (vi) determining a class to which a given set of vectors belongs based on a previously performed action that is associated with the given class.

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:

fourth 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:

fifth 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.