Classification using probability estimate re-sampling
First Claim
1. A computer-implemented method of calculating estimates of a joint posterior probability of class membership given combinations of attribute values of a pair of attributes, the calculating being performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome, the method comprising:
- a) calculating first estimates of a posterior probability of class membership given attribute values of a first attribute of the pair;
b) calculating second estimates of a posterior probability of class membership given attribute values of a second attribute of the pair;
c) binning the first estimates into a plurality of first probability range bins;
d) binning the second estimates into a plurality of second probability range bins;
e) creating a mapping of instances of the training set mapped to combinations of one of each of the first and second pluralities of probability range bins; and
f) on the basis of said mapping, calculating estimates of a joint posterior probability of class membership given membership in the combinations of first and second probability range bins.
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Abstract
Embodiments of a computer-implemented method of calculating estimates of a joint posterior probability of class membership given combinations of attribute values of a pair of attributes are disclosed. The calculating is performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome. Embodiments of the method comprise calculating first and second estimates of a posterior probability of class membership given attribute values of a first and second attribute of the pair, respectively, and binning the first and second estimates into a respective plurality of first and second probability range bins. Instances of the training set are mapped to combinations of one of each of the first and second pluralities of probability range bins, and on the basis of the mapping, calculating estimates of a joint posterior probability of class membership.
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Citations
17 Claims
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1. A computer-implemented method of calculating estimates of a joint posterior probability of class membership given combinations of attribute values of a pair of attributes, the calculating being performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome, the method comprising:
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a) calculating first estimates of a posterior probability of class membership given attribute values of a first attribute of the pair;
b) calculating second estimates of a posterior probability of class membership given attribute values of a second attribute of the pair;
c) binning the first estimates into a plurality of first probability range bins;
d) binning the second estimates into a plurality of second probability range bins;
e) creating a mapping of instances of the training set mapped to combinations of one of each of the first and second pluralities of probability range bins; and
f) on the basis of said mapping, calculating estimates of a joint posterior probability of class membership given membership in the combinations of first and second probability range bins. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 15)
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2. A computer-implemented method of calculating estimates of a joint posterior probability of class membership given combinations of attribute values of a triplet of attributes, the calculating being performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome, the method comprising:
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a) calculating first estimates of a posterior probability of class membership given attribute values of a first attribute of the triplet;
b) calculating second estimates of a posterior probability of class membership given attribute values of a second attribute of the triplet;
c) calculating third estimates of a posterior probability of class membership given attribute values of a third attribute of the triplet;
d) binning the first estimates into a plurality of first probability range bins;
e) binning the second estimates into a plurality of second probability range bins;
f) binning the third estimates into a plurality of third probability range bins;
g) creating a mapping of instances of the training set mapped to combinations of one of each of the first, second and third pluralities of probability range bins; and
h) on the basis of said mapping, calculating estimates of a joint posterior probability of class membership given membership in the combinations of first, second and third probability range bins.
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11. A computer readable storage medium having stored thereon instructions and data which, when executed by a computer, cause the computer to calculate estimates of a joint posterior probability of class membership given combinations of attribute values of a pair of attributes, the calculating being performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome, and the calculating comprising:
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a) calculating first estimates of a posterior probability of class membership given attribute values of a first attribute of the pair;
b) calculating second estimates of a posterior probability of class membership given attribute values of a second attribute of the pair;
c) binning the first estimates into a plurality of first probability range bins;
d) binning the second estimates into a plurality of second probability range bins;
e) creating a mapping of instances of the training set mapped to combinations of one of each of the first and second pluralities of probability range bins; and
f) on the basis of said mapping, calculating estimates of a joint posterior probability of class membership given membership in the combinations of first and second probability range bins.
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12. A computer arranged to calculate estimates of a joint posterior probability of class membership given combinations of attribute values of a pair of attributes, the calculating being performed on the basis of data representing a training set of a plurality of instances defined by attribute values for a plurality of attributes together with a class membership outcome, and the calculating comprising:
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a) calculating first estimates of a posterior probability of class membership given attribute values of a first attribute of the pair;
b) calculating second estimates of a posterior probability of class membership given attribute values of a second attribute of the pair;
c) binning the first estimates into a plurality of first probability range bins;
d) binning the second estimates into a plurality of second probability range bins;
e) creating a mapping of instances of the training set mapped to combinations of one of each of the first and second pluralities of probability range bins; and
f) on the basis of said mapping, calculating estimates of a joint posterior probability of class membership given membership in the combinations of first and second probability range bins.
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16. A computer-implemented method of generating a model for use in classifying data representing a new instance, the model being generated on the basis of data representing a training set of a plurality of instances, each comprising attribute values for at least a first and a second attribute together with a class membership outcome, the method comprising:
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a) calculating values of first estimates of a posterior probability of class membership given attribute values of the first attribute;
b) calculating values of second estimates of a posterior probability of class membership given attribute values of the second attribute;
c) mapping data corresponding to instances of the training set to data corresponding to the combined values of the first and second estimates; and
d) calculating values of estimates of a joint posterior probability of class membership given the data corresponding to the combined values of the first and second estimates. - View Dependent Claims (17)
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Specification