US 2018/0121811 A1 · PROFILING A POPULATION OF EXAMPLES IN A PRECISELY DESCRIPTIVE OR TENDENCY-BASED MANNER

Abstract

A computer-implemented method for profiling a population of examples includes a computer system creating a rule collection comprising a plurality of rules, wherein each rule describes a respective corresponding sub-population of the examples according to a conjunction of a plurality of feature-value pairs. The computer system generates a precisely descriptive profile by performing a search process on the rule collection to identify a rule that either maximizes or minimizes the value of a user-specified target feature in the respective corresponding sub-population.

Claims23

Dependent claims

A computer-implemented method for profiling a population of examples, the method comprising:

creating, by a computer system, a rule collection comprising a plurality of rules, wherein each rule describes a respective corresponding sub-population of the examples according to a conjunction of a plurality of feature-value pairs;
and
generating, by the computer system, a precisely descriptive profile by performing a search process on the rule collection to identify a rule that either maximizes or minimizes a value of a user-specified target feature in the respective corresponding sub-population.

A computer-implemented method for profiling a population of examples, the method comprising:

receiving, by a computer system, a user-specified target feature;
determining, by the computer system, a performance measurement for each example in the population with regards to the user-specified target feature;
identifying, by the computer system, a sub-population of the examples based on the performance measurement determined for each example, wherein the sub-population comprises one of (i) highest performers with respect to the user-specified target feature or (ii) lowest performers with respect to the user-specified target feature;
determining, by the computer system, a population mean value for the user-specified target feature across the population;
identifying, by the computer system, feature-value pairs from the sub-population that deviate from the population mean value by more than a predetermined threshold value;
and
displaying the identified feature-value pairs.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application

15/563,305Filed 4 Apr 2016

Priority

3 Apr 2015

Published

3 May 2018

Term ends

Not estimatedThe source records don’t support an estimate.

Classification9 codes

G06N 5/025
Knowledge engineering; Knowledge acquisition: extracting rules from data
G06F 7/02
Methods or arrangements for processing data by operating upon the order or content of the data handled: comparing digital values
G06N 5/01
Computing arrangements using knowledge-based models: dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
G06N 20/00
Machine learning

Profiling a population of examples in a precisely descriptive or tendency-based manner

Life of this patent

Profiling a population of examples in a precisely descriptive or tendency-based manner

Life of this patent

Abstract

Claims23