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公开(公告)号：US11003947B2
公开(公告)日：2021-05-11
申请号：US16285173
申请日：2019-02-25
发明人： Scott Zoldi , Shafi Rahman
摘要： A system and method for learning and associating reliability and confidence corresponding to a model's predictions by examining the support associated with datapoints in the variable phase space in terms of data coverage, and their impact on the weights distribution. The approach disclosed herein examines the impact of minor perturbations on a small fraction of the training exemplars in the variable phase space on the weights to understand whether the weights remain unperturbed or change significantly.
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2.发明申请公开(公告)号：US20190354853A1
公开(公告)日：2019-11-21
申请号：US15985130
申请日：2018-05-21
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： Systems and methods that use a neural network architecture for extracting interpretable relationships among predictive input variables. This leads to neural network models that are interpretable and explainable. More importantly, these systems and methods lead to discovering new interpretable variables that are functions of predictive input variables, which in turn can be extracted as new features and utilized in other types of interpretable models, like scorecards (fraud score, etc.), but with higher predictive power than conventional systems and methods.
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公开(公告)号：US20140351044A1
公开(公告)日：2014-11-27
申请号：US13901467
申请日：2013-05-23
发明人： Shafi Rahman , Amit Kiran Sowani , Rakhi Agrawal , Manmeet Kaur
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0261 , G06Q30/0255
摘要： The current subject matter relates to generation of relevant real-time offers based on global positioning system (GPS) data of an individual. A mobile device of an individual can record the GPS data of the individual. The mobile device can be connected to a central system. The central system can receive the recorded GPS data. The central system can predict, by using a trained predictive model and based on transaction history of the individual and the GPS data, categories of likely purchases by the individual. The central system can generate or reproduce offers from merchants of the predicted categories that are located within a threshold distance from a current location of the individual. The central system can send the generated offers to the mobile device that can display the generated offers in real-time. Other applications can include improving relevance of batch offers and/or real-time offers based on a recent purchase trigger.
摘要翻译： 目前的主题涉及基于个人的全球定位系统（GPS）数据的相关实时报价的生成。 个人的移动设备可以记录个人的GPS数据。 移动设备可以连接到中央系统。 中央系统可以接收记录的GPS数据。 中央系统可以通过使用经过训练的预测模型并基于个人的交易历史和GPS数据预测个人可能的购买类别。 中央系统可以生成或复制来自商户的预测类别的报价，这些预测类别位于距离个体的当前位置的阈值距离内。 中央系统可以将生成的报价发送给可以实时显示生成的报价的移动设备。 其他应用程序可以包括根据最近的购买触发提高批次报价和/或实时报价的相关性。
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公开(公告)号：US11574234B2
公开(公告)日：2023-02-07
申请号：US16128359
申请日：2018-09-11
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： A model governance framework uses a shared ledger on the back of a blockchain. The solution tracks various analytic tracking documents (ATDs) and associated assets, like requirements and sprints, through various stages of an ATD lifecycle. Data schema and data distributions are also tracked. The decision models, corresponding variables and execution codes are also tracked. Existing variables and execution codes are made available via a preexisting asset ATD for reuse. Various transactions provide mechanism for accessing and manipulating the various assets through a recorded ledger of events and approvals. A system provides tracking of the approvals and the approvers of all model assets that are touched by any participant, and further provides access control and security for multi-user access. An application layer provides graphical access to the various aspects of the blockchain. Event notification provides the backbone for interfacing with various external systems like email servers and version control systems.
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公开(公告)号：US11151450B2
公开(公告)日：2021-10-19
申请号：US15985130
申请日：2018-05-21
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： Systems and methods that use a neural network architecture for extracting interpretable relationships among predictive input variables. This leads to neural network models that are interpretable and explainable. More importantly, these systems and methods lead to discovering new interpretable variables that are functions of predictive input variables, which in turn can be extracted as new features and utilized in other types of interpretable models, like scorecards (fraud score, etc.), but with higher predictive power than conventional systems and methods.
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公开(公告)号：US10956940B2
公开(公告)日：2021-03-23
申请号：US13901467
申请日：2013-05-23
发明人： Shafi Rahman , Amit Kiran Sowani , Rakhi Agrawal , Manmeet Kaur
IPC分类号： G06Q30/02
摘要： The current subject matter relates to generation of relevant real-time offers based on global positioning system (GPS) data of an individual. A mobile device of an individual can record the GPS data of the individual. The mobile device can be connected to a central system. The central system can receive the recorded GPS data. The central system can predict, by using a trained predictive model and based on transaction history of the individual and the GPS data, categories of likely purchases by the individual. The central system can generate or reproduce offers from merchants of the predicted categories that are located within a threshold distance from a current location of the individual. The central system can send the generated offers to the mobile device that can display the generated offers in real-time. Other applications can include improving relevance of batch offers and/or real-time offers based on a recent purchase trigger.
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公开(公告)号：US11468260B2
公开(公告)日：2022-10-11
申请号：US17307834
申请日：2021-05-04
发明人： Scott Zoldi , Shafi Rahman
摘要： Computer-implemented systems and methods for selecting a first neural network model from a set of neural network models for a first dataset, the first neural network model having a set of predictor variables and a second dataset comprising a plurality of datapoints mapped into a multi-dimensional grid that defines one or more neighborhood data regions; applying the first neural network model on the first dataset to generate a model score for one or more datapoints in the second dataset, the model score representing an optimal fit of input predictor variables to a target variable for the set of variables of the first neural network model.
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公开(公告)号：US11354292B2
公开(公告)日：2022-06-07
申请号：US15981755
申请日：2018-05-16
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： A system and method for analyzing coverage, bias and model explanations in large dimensional modeling data includes discretizing three or more variables of a dataset to generate a discretized phase space represented as a grid of a plurality of cells, the dataset comprising a plurality of records, each record of the plurality of records having a value and a unique identifier (ID). A grid transformation is applied to each record in the dataset to assign each record to a cell of the plurality of cells of the grid according to the grid transformation. A grid index is generated to reference each cell using a discretized feature vector. A grid storage for storing the records assigned to each cell of the grid is then created. The grid storage using the ID of each record as a reference to each record and the discretized feature vector as a key to each cell.
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公开(公告)号：US20210342635A1
公开(公告)日：2021-11-04
申请号：US17307834
申请日：2021-05-04
发明人： Scott Zoldi , Shafi Rahman
摘要： Computer-implemented systems and methods for selecting a first neural network model from a set of neural network models for a first dataset, the first neural network model having a set of predictor variables and a second dataset comprising a plurality of datapoints mapped into a multi-dimensional grid that defines one or more neighborhood data regions; applying the first neural network model on the first dataset to generate a model score for one or more datapoints in the second dataset, the model score representing an optimal fit of input predictor variables to a target variable for the set of variables of the first neural network model.
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公开(公告)号：US20200082302A1
公开(公告)日：2020-03-12
申请号：US16128359
申请日：2018-09-11
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： A model governance framework uses a shared ledger on the back of a blockchain. The solution tracks various analytic tracking documents (ATDs) and associated assets, like requirements and sprints, through various stages of an ATD lifecycle. Data schema and data distributions are also tracked. The decision models, corresponding variables and execution codes are also tracked. Existing variables and execution codes are made available via a preexisting asset ATD for reuse. Various transactions provide mechanism for accessing and manipulating the various assets through a recorded ledger of events and approvals. A system provides tracking of the approvals and the approvers of all model assets that are touched by any participant, and further provides access control and security for multi-user access. An application layer provides graphical access to the various aspects of the blockchain. Event notification provides the backbone for interfacing with various external systems like email servers and version control systems.
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