公开(公告)号：US07349919B2

公开(公告)日：2008-03-25

申请号：US10719820

申请日：2003-11-21

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F7/00 ,  G06F17/00

CPC分类号： G06F17/30598 ,  Y10S707/99943

摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

摘要翻译： 一种用于生成数据挖掘模型的计算机化方法，系统和程序产品。 用户可以为模型和样本数据提供目标，以训练，验证和测试模型。 规则系统可以根据目标和/或样本数据自动选择一组算法。 也可以从样本数据创建多个数据集。 使用数据集，可以为要使用的特定数据优化算法集合。 然后可以从优化的算法集合生成数据挖掘模型。

公开(公告)号：US07743068B2

公开(公告)日：2010-06-22

申请号：US11923843

申请日：2007-10-25

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F7/00 ,  G06F17/00

CPC分类号： G06F17/30598 ,  Y10S707/99943

摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

公开(公告)号：US07523106B2

公开(公告)日：2009-04-21

申请号：US10720792

申请日：2003-11-24

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  Marcelo Cunha Loureiro ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  Marcelo Cunha Loureiro ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F17/30

CPC分类号： G06F17/30539 ,  G06F2216/03 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935 ,  Y10S707/99943

摘要： Under the present invention, a data exploration system, a customized model system and an existing model system are provided. The data exploration system analyzes user data to identify statistical information such as data distribution, data relationships, data outliners and invalid or missing data values. The customized model center iteratively generates customized data mining models in parallel based on permutations of the user data, user-provided business parameters and/or a set of model generation algorithms. The existing model system provides users with a library of existing data mining models, assembled based on the business parameters, from which they can choose one or more. In any event, any customized or existing data mining models selected can be run against the user data in parallel.

摘要翻译： 在本发明的基础上，提供了数据挖掘系统，定制模型系统和现有的模型系统。 数据挖掘系统分析用户数据以识别统计信息，如数据分布，数据关系，数据外链以及无效或丢失的数据值。 定制模型中心根据用户数据的排列，用户提供的业务参数和/或一组模型生成算法，迭代地并行生成定制的数据挖掘模型。 现有的模型系统为用户提供了现有数据挖掘模型库，根据业务参数进行组合，从中可以选择一个或多个。 无论如何，可以并行地针对用户数据运行任何定制或现有的数据挖掘模型。

公开(公告)号：US07739297B2

公开(公告)日：2010-06-15

申请号：US11923853

申请日：2007-10-25

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F7/00 ,  G06F17/00

CPC分类号： G06F17/30598 ,  Y10S707/99943

摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

公开(公告)号：US07734645B2

公开(公告)日：2010-06-08

申请号：US11923862

申请日：2007-10-25

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  John A. Medicke, Jr. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F7/00 ,  G06F17/00

CPC分类号： G06F17/30598 ,  Y10S707/99943

摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

摘要翻译： 一种用于生成数据挖掘模型的计算机化方法，系统和程序产品。 用户可以为模型和样本数据提供目标，以训练，验证和测试模型。 规则系统可以根据目标和/或样本数据自动选择一组算法。 也可以从样本数据创建多个数据集。 使用数据集，可以为要使用的特定数据优化算法集合。 然后可以从优化的算法集合生成数据挖掘模型。

公开(公告)号：US20090144276A1

公开(公告)日：2009-06-04

申请号：US12348580

申请日：2009-01-05

申请人： Feng-wei Chen Russell ,  Ameet M. Kini ,  Marcelo Cunha Loureiro ,  John A. Medicke, JR. ,  Betsy M. Plunket ,  Ashish Sureka

发明人： Feng-wei Chen Russell ,  Ameet M. Kini ,  Marcelo Cunha Loureiro ,  John A. Medicke, JR. ,  Betsy M. Plunket ,  Ashish Sureka

IPC分类号： G06F17/30

CPC分类号： G06F16/2465 ,  G06F2216/03 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935 ,  Y10S707/99943

摘要： Under the present invention, a data exploration system, a customized model system and an existing model system are provided. The data exploration system analyzes user data to identify statistical information such as data distribution, data relationships, data outliners and invalid or missing data values. The customized model center iteratively generates customized data mining models in parallel based on permutations of the user data, user-provided business parameters and/or a set of model generation algorithms. The existing model system provides users with a library of existing data mining models, assembled based on the business parameters, from which they can choose one or more. In any event, any customized or existing data mining models selected can be run against the user data in parallel.

摘要翻译： 在本发明的基础上，提供了数据挖掘系统，定制模型系统和现有的模型系统。 数据挖掘系统分析用户数据以识别统计信息，如数据分布，数据关系，数据外链以及无效或丢失的数据值。 定制模型中心根据用户数据的排列，用户提供的业务参数和/或一组模型生成算法，迭代地并行生成定制的数据挖掘模型。 现有的模型系统为用户提供了现有数据挖掘模型库，根据业务参数进行组合，从中可以选择一个或多个。 无论如何，可以并行地针对用户数据运行任何定制或现有的数据挖掘模型。