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公开(公告)号：US20180247226A1
公开(公告)日：2018-08-30
申请号：US15756902
申请日：2015-09-04
Applicant: ENTIT Software LLC
Inventor： George Forman , Hila Nachlieli
CPC classification number: G06N20/00 , G06K9/6256 , G06K9/6262 , G06K9/6267
Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises receiving a training dataset of cases, where each of a plurality of classes is associated with a set of labeled cases in the training dataset. The method also comprises defining a proper subset of classes in the training dataset, and training a first classifier model on the proper subset of classes in the training dataset. The method further comprises testing the first classifier model on at least one class in the training dataset that was excluded from the proper subset, and determining a performance measurement of the first classifier model.
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公开(公告)号：US11449789B2
公开(公告)日：2022-09-20
申请号：US16077591
申请日：2016-02-16
Applicant: ENTIT SOFTWARE LLC
Inventor： George Forman , Hila Nachlieli
Abstract: An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.
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公开(公告)号：US20190057321A1
公开(公告)日：2019-02-21
申请号：US16077591
申请日：2016-02-16
Applicant: ENTIT SOFTWARE LLC
Inventor： George Forman , Hila Nachlieli
Abstract: An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.
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