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1. 发明授权

US09020861B2 Predictive model application programming interface 有权
标题翻译：预测模型应用程序编程接口
公开(公告)号：US09020861B2
公开(公告)日：2015-04-28
申请号：US13486217
申请日：2012-06-01
申请人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F17/00 , G06F17/20 , G06N99/00 , G06F17/24
CPC分类号： G06N99/005 , G06F17/246
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for utilizing predictive models from an application scripting language.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于利用来自应用程序脚本语言的预测模型。

2. 发明授权

US08694540B1 Predictive analytical model selection 有权
标题翻译：预测分析模型选择
公开(公告)号：US08694540B1
公开(公告)日：2014-04-08
申请号：US13246410
申请日：2011-09-27
申请人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F17/30
CPC分类号： G06F17/30292
摘要： A computer-implemented method includes obtaining a database table, the database table including data arranged in a plurality of rows and a plurality of columns, each column of data being associated with a different tag that specifies a category for data in the column, using one or more processors to identify a first predictive model, from a collection of predictive models, that can be applied to the database table to generate a predictive output, in which identifying the first predictive model is based on one or more of the different tags, adding a name associated with the first predictive model to a set of names of predictive models that are compatible with the database table, and providing the set of names of predictive models to a client device.
摘要翻译：计算机实现的方法包括获得数据库表，数据库表包括以多行和多列排列的数据，每列数据与指定列中的数据的类别的不同标签相关联，使用一个或多个处理器，以从预测模型集合中识别可以应用于数据库表以产生预测输出的第一预测模型，其中识别第一预测模型基于一个或多个不同标签，添加与第一预测模型相关联的名称与与数据库表兼容的预测模型的一组名称，以及将预测模型的名称集合提供给客户端设备。

3. 发明授权

US08583576B1 Predictive model importation 有权
公开(公告)号：US08583576B1
公开(公告)日：2013-11-12
申请号：US13482196
申请日：2012-05-29
申请人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F15/18 , G06E1/00 , G06E3/00 , G06G7/00
CPC分类号： G06N3/08 , G06N99/005
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a plurality of model representations of predictive models, each model representation associated with a respective user and expresses a respective predictive model, and selecting a model implementation for each of the model representations based on one or more system usage properties associated with the user associated with the corresponding model representation.

4. 发明授权

US08370280B1 Combining predictive models in predictive analytical modeling 有权
标题翻译：将预测模型结合在预测分析建模中
公开(公告)号：US08370280B1
公开(公告)日：2013-02-05
申请号：US13252063
申请日：2011-10-03
申请人： Wei-Hao Lin , Travis H. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A method can include the actions of: receiving a feature vector, the feature vector including one or more elements; identifying an element type for each of the one or more elements; selecting, from a set of predictive models, a subset of one or more predictive models based on the element types and one or more performance indicators associated with each predictive model in the set of predictive models; processing the feature vector using the subset of predictive models, each predictive model of the subset of predictive models generating an output based on the feature vector to provide a plurality of outputs; and generating a final output based on the plurality of outputs. Other embodiments may include corresponding systems, apparatus, and computer program products for executing the method.
摘要翻译：方法可以包括以下动作：接收特征向量，所述特征向量包括一个或多个元素; 识别所述一个或多个元素中的每个元素的元素类型; 基于所述元素类型和与所述一组预测模型中的每个预测模型相关联的一个或多个性能指标，从一组预测模型中选择一个或多个预测模型的子集; 使用所述预测模型的子集处理所述特征向量，所述预测模型子集的每个预测模型基于所述特征向量生成输出以提供多个输出; 以及基于所述多个输出生成最终输出。其他实施例可以包括用于执行该方法的相应系统，装置和计算机程序产品。

5. 发明申请

US20120284212A1 Predictive Analytical Modeling Accuracy Assessment 审中-公开
标题翻译：预测分析建模精度评估
公开(公告)号：US20120284212A1
公开(公告)日：2012-11-08
申请号：US13101040
申请日：2011-05-04
申请人： Wei-Hao Lin , Travis Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F15/18
CPC分类号： G06N20/00
摘要： A system includes a computer(s) coupled to a data storage device(s) that stores a training function repository and a predictive model repository that includes includes updateable trained predictive models each associated with an accuracy score. A series of training data sets are received, being training samples each having output data that corresponds to input data. The training data is different from initial training data that was used with training functions from the repository to train the predictive models initially. Upon receiving a first training data set included in the series and for each predictive model in the repository, the input data in the first training set is used to generate predictive output data that is compared to the output data. Based on the comparison and previous comparisons determined from the initial training data and from previously received training data sets, an updated accuracy score for each predictive model is determined.
摘要翻译：系统包括耦合到存储训练功能存储库的数据存储设备的计算机和包括可更新训练的预测模型的预测模型存储库，每个与精度分数相关联。接收一系列训练数据组，训练样本，每个训练样本都具有与输入数据相对应的输出数据。培训数据与初始培训数据不同，初始训练数据与仓库的培训功能一起使用，以初步训练预测模型。在接收到包括在系列中的第一训练数据集和存储库中的每个预测模型时，第一训练集中的输入数据用于产生与输出数据进行比较的预测输出数据。基于从初始训练数据和先前接收到的训练数据集确定的比较和先前比较，确定每个预测模型的更新的精度得分。

6. 发明授权

US08209271B1 Predictive model training on large datasets 有权
标题翻译：大型数据集的预测模型训练
公开(公告)号：US08209271B1
公开(公告)日：2012-06-26
申请号：US13249725
申请日：2011-09-30
申请人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H. K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： Methods, systems, and apparatus, including computer programs stored on a computer storage medium, for training predictive models using large datasets.
摘要翻译：方法，系统和装置，包括存储在计算机存储介质上的计算机程序，用于使用大数据集训练预测模型。

7. 发明授权

US08204851B2 Method and system for providing a graphical workflow monitor 有权
标题翻译：用于提供图形工作流监视器的方法和系统
公开(公告)号：US08204851B2
公开(公告)日：2012-06-19
申请号：US11695412
申请日：2007-04-02
申请人： Ruowen Rong , Lingrong Chen , Gang Fu
发明人： Ruowen Rong , Lingrong Chen , Gang Fu
IPC分类号： G06F17/30
CPC分类号： G06Q10/06
摘要： A browser based workflow monitor uses a graphical user interface (GUI) to display workflow status information and to create log information. The monitor presents the log information to a user in a format that is easily understood. Workflow information is accessed from a user workstation via a data network and displayed within a browser application.
摘要翻译：基于浏览器的工作流监视器使用图形用户界面（GUI）来显示工作流状态信息并创建日志信息。监视器以易于理解的格式向用户显示日志信息。通过数据网络从用户工作站访问工作流信息，并在浏览器应用程序中显示。

8. 发明申请

US20080027962A1 Method and system for providing network based transaction metrics 有权
标题翻译：提供基于网络的事务度量的方法和系统
公开(公告)号：US20080027962A1
公开(公告)日：2008-01-31
申请号：US11496090
申请日：2006-07-31
申请人： Ruowen Rong , Lingrong Chen , Gang Fu
发明人： Ruowen Rong , Lingrong Chen , Gang Fu
IPC分类号： G06F7/00
CPC分类号： G06Q30/02
摘要： An approach is provided for metrics data collection for business transactions. An online activity (e.g., Application Programming Interface (API) call) associated with a business flow is identified. It is determined whether the online activity is a part of a transaction, wherein the transaction is defined according to a business rule. Status of the transaction is updated if the online activity is a part of the transaction.
摘要翻译：为业务交易的度量数据收集提供了一种方法。识别与业务流相关联的在线活动（例如，应用程序编程接口（API）调用）。确定在线活动是否是交易的一部分，其中根据业务规则定义交易。如果在线活动是交易的一部分，交易的状态将被更新。

9. 发明申请

US20150170048A1 Determining a Type of Predictive Model for Training Data 审中-公开
标题翻译：确定训练数据的预测模型类型
公开(公告)号：US20150170048A1
公开(公告)日：2015-06-18
申请号：US13209358
申请日：2011-08-12
申请人： Wei-Hao Lin , Travis H.K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
发明人： Wei-Hao Lin , Travis H.K. Green , Robert Kaplow , Gang Fu , Gideon S. Mann
IPC分类号： G06N99/00 , G06N5/04
CPC分类号： G06N20/00 , H04L51/12
摘要： A computer-implemented method includes receiving, in a system of one or more computers, training data for predictive modeling, the training data including a plurality of categories; determining, by the system, one or more attributes of the training data; identifying, by the system in a mapping of attributes to types of predictive models, a type of predictive model that is mapped to at least one of the one or more attributes; obtaining a utility function for the predictive model of the identified type, the utility function specifying importance of the plurality of categories relative to each other; and generating, based on the training data and the utility function, a predictive model of the identified type.
摘要翻译：计算机实现的方法包括在一个或多个计算机的系统中接收用于预测建模的训练数据，所述训练数据包括多个类别; 由系统确定训练数据的一个或多个属性; 在属性到预测模型的类型的映射中由系统识别被映射到一个或多个属性中的至少一个的预测模型的类型; 获得用于所识别类型的预测模型的效用函数，所述效用函数指定所述多个类别相对于彼此的重要性; 并且基于训练数据和效用函数生成所识别类型的预测模型。

10. 发明授权

US08909564B1 Predictive model evaluation and training based on utility 有权
标题翻译：基于效用的预测模型评估与训练
公开(公告)号：US08909564B1
公开(公告)日：2014-12-09
申请号：US13224245
申请日：2011-09-01
申请人： Robert Kaplow , Wei-Hao Lin , Gideon S. Mann , Travis H. K. Green , Gang Fu , Robbie A. Haertel
发明人： Robert Kaplow , Wei-Hao Lin , Gideon S. Mann , Travis H. K. Green , Gang Fu , Robbie A. Haertel
IPC分类号： G06F15/18 , G06F19/24
CPC分类号： G06N99/005 , G06N5/04 , G06N5/043
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a plurality of different types of predictive models using training data, wherein each of the predictive models implements a different machine learning technique. One or more weights are obtained wherein each weight is associated with an answer category in the plurality of examples. A weighted accuracy is calculated for each of the predictive models using the one or more weights.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于使用训练数据训练多种不同类型的预测模型，其中每个预测模型实现不同的机器学习技术。获得一个或多个权重，其中每个权重与多个示例中的答案类别相关联。使用一个或多个权重对每个预测模型计算加权精度。

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