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公开(公告)号：US20210357803A1
公开(公告)日：2021-11-18
申请号：US16876278
申请日：2020-05-18
摘要： Embodiments relate to a system, program product, and method for generating an enhanced feature catalog for a predictive model. The embodiments disclosed herein include capturing predictive model design time information including training data lineage metadata to determine the features of the training data, model design time measurements, and model design time metadata. Once the predictive model is built, the training data lineage metadata is used to capture the features that will be maintained within a feature catalog. The model design time measurements and model design time metadata provide further correlation between the predictive model and the features. Runtime metrics on the predictive model create additional correlations between the captured data and metadata with the features in the feature catalog to expeditiously identify the relevant features of the predictive model.
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公开(公告)号：US20210287131A1
公开(公告)日：2021-09-16
申请号：US16814603
申请日：2020-03-10
摘要： A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to run a machine learning base model on input data to generate base model prediction data and run a machine learning error prediction model on the input data to generate error prediction data. The at least one processor is configured to execute the instructions to generate predicted correct base model prediction data based on the base model prediction data and the error prediction data. The at least one processor is configured to execute the instructions to generate confusion values data based on the base model prediction data and the predicted correct base model prediction data. The at least one processor is also configured to execute the instructions to generate base model accuracy fairness metrics data based on the confusion values data.
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53.发明申请公开(公告)号：US20210286945A1
公开(公告)日：2021-09-16
申请号：US16817974
申请日：2020-03-13
发明人： Seema Nagar , Kuntal Dey , Nishtha Madaan , Manish Anand Bhide , Sameep Mehta , Diptikalyan Saha
IPC分类号： G06F40/279 , G06N20/00 , G06Q50/00 , G06Q30/06 , G06Q30/02 , G06Q10/08 , G06F40/166
摘要： According to one embodiment of the present invention, a system for modifying content associated with an item comprises at least one processor. Features of interest of the item to a plurality of different groups are determined based on user comments produced by members of the plurality of different groups. The members within each group have a common characteristic. The features of interest to each group within the content associated with the item are identified, and the content associated with the item is modified by balancing the features of interest to the plurality of different groups within the content associated with the item. Embodiments of the present invention further include a method and computer program product for modifying content associated with an item in substantially the same manner described above.
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公开(公告)号：US20210279607A1
公开(公告)日：2021-09-09
申请号：US16813512
申请日：2020-03-09
摘要： A computer-implemented method according to one embodiment includes identifying an occurrence of accuracy drift by a trained model; identifying data associated with the accuracy drift, utilizing a drift detection model (DDM) constructed for the trained model; applying the data associated with the accuracy drift to a decision tree to determine a feature space and specific subset of the data causing the accuracy drift; analyzing a distribution of features within the feature space for the specific subset of the data causing the accuracy drift to determine specific features of the data causing the accuracy drift; and returning the specific features of the data causing the accuracy drift.
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公开(公告)号：US20210004311A1
公开(公告)日：2021-01-07
申请号：US16460182
申请日：2019-07-02
摘要： Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
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公开(公告)号：US20200372056A1
公开(公告)日：2020-11-26
申请号：US16421131
申请日：2019-05-23
发明人： Manish Anand Bhide , Kuntal Dey , Nishtha Madaan , Seema Nagar , Sameep Mehta
摘要： A processor may receive a record. The record may include one or more segments of text. The processor may tag each segment of text with an indicator. The indicator may denote a specific instance of bias in each of a respective segment of text. The processor may automatically generate a summary of the record. The summary of the record may include a set of segments of text. The set of segments of text may have a different overall bias than the record. The processor may display the summary of the record to a user.
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公开(公告)号：US12130721B2
公开(公告)日：2024-10-29
申请号：US17347651
申请日：2021-06-15
IPC分类号： G06F11/36
CPC分类号： G06F11/3604
摘要： A computer-implemented method includes: receiving, by a computing device and from a user device, a request to validate an application program interface (API); validating, by the computing device, the API by performing a fetch analysis using different user profiles; returning, by the computing device and to the user device, a result of the fetch analysis; validating, by the computing device, the API by performing an insert/update analysis using the different user profiles; and returning, by the computing device and to the user device, a result of the insert/update analysis.
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公开(公告)号：US20240249187A1
公开(公告)日：2024-07-25
申请号：US18158190
申请日：2023-01-23
IPC分类号： G06N20/00
CPC分类号： G06N20/00
摘要： Provided are techniques for correcting a classification model. For each original record of a plurality of original records that are processed by a classification model: the original record is perturbed; for the original record, an original confidence value is obtained for each class of a plurality of classes; for the perturbed record, a perturbed confidence value is obtained for each class of the plurality of classes; a final confidence value is determined using each original confidence value, each perturbed confidence value, and a direction of distance travelled; and a determination is made of whether the original record is biased based on the final confidence value. Then, it is determined whether the classification model is biased based on the original records that are determined to be biased. In response to determining that the classification model is biased, the classification model is corrected, otherwise, the classification model is deployed.
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公开(公告)号：US12047673B2
公开(公告)日：2024-07-23
申请号：US17648726
申请日：2022-01-24
发明人： Phani Kumar V. U. Ayyagari , Harikrishna Manchineni , Sai Prasanth Vuppala , Manish Anand Bhide
CPC分类号： H04N23/64 , G06K7/1417 , G06K7/1443 , G06V30/10
摘要： In an approach, a processor receives a photograph requirement from an image of an application, the photograph requirement associated with a photograph to be uploaded to the application. A processor adjusts a camera setting based on the photograph requirement. A processor captures the photograph in accordance with the adjusted camera setting.
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公开(公告)号：US12014287B2
公开(公告)日：2024-06-18
申请号：US17111757
申请日：2020-12-04
CPC分类号： G06N5/04 , G06F16/2379 , G06N20/00
摘要： A system and related method score a fairness of an outcome model. The method comprises receiving a set of original transaction records (OTRs), and selecting an OTR subset of the OTRs according to a subset selection criteria in order to reduce a number of OTRs to send to outcome model. For each OTR in the subset a perturbed transaction record (PTR) is created based on the OTR that includes changing at least one attribute in the PTR from the OTR, sending the OTR and the PTR to the outcome model, receiving an OTR outcome and a PTR outcome from the outcome model, and determining a record bias score for the OTR outcome and the PTR outcome respectively that indicates bias in the respective outcome. The OTR and the PTR bias score are stored in a bias determination system (BDS) database.
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