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1. 发明申请

US20110307422A1 EXPLORING DATA USING MULTIPLE MACHINE-LEARNING MODELS 有权
标题翻译：使用多种机器学习模型探索数据
公开(公告)号：US20110307422A1
公开(公告)日：2011-12-15
申请号：US12797395
申请日：2010-06-09
申请人： Steven Mark Drucker , Kayur Dushyant Patel , Desney S. Tan , Ashish Kapoor , James Anthony Fogarty
发明人： Steven Mark Drucker , Kayur Dushyant Patel , Desney S. Tan , Ashish Kapoor , James Anthony Fogarty
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A multiple model data exploration system and method for running multiple machine-learning models simultaneously to understand and explore data. Embodiments of the system and method allow a user to gain a greater understanding of the data and to gain new insights into their data. Embodiments of the system and method also allow a user to interactively explore the problem and to navigate different views of data. Many different classifier training and evaluation experiments are run simultaneously and results are obtained. The results are aggregated and visualized across each of the experiments to determine and understand how each example is classified for each different classifier. These results then are summarized in a variety of ways to allow users to obtain a greater understanding of the data both in terms of the individual examples themselves and features associated with the data.
摘要翻译：一种用于同时运行多个机器学习模型的多模型数据挖掘系统和方法，用于理解和探索数据。该系统和方法的实施例允许用户更好地理解数据并获得对其数据的新见解。系统和方法的实施例还允许用户交互地探索问题并导航数据的不同视图。同时运行许多不同的分类器训练和评估实验，得到结果。结果在每个实验中进行聚合和可视化，以确定和理解每个示例如何分类给每个不同的分类器。然后以各种方式总结这些结果，以允许用户在各个示例本身和与数据相关的特征方面获得对数据的更多了解。

2. 发明授权

US08595153B2 Exploring data using multiple machine-learning models 有权
标题翻译：使用多机器学习模型探索数据
公开(公告)号：US08595153B2
公开(公告)日：2013-11-26
申请号：US12797395
申请日：2010-06-09
申请人： Steven Mark Drucker , Kayur Dushyant Patel , Desney S. Tan , Ashish Kapoor , James Anthony Fogarty
发明人： Steven Mark Drucker , Kayur Dushyant Patel , Desney S. Tan , Ashish Kapoor , James Anthony Fogarty
IPC分类号： G06N5/00
CPC分类号： G06N99/005
摘要： A multiple model data exploration system and method for running multiple machine-learning models simultaneously to understand and explore data. Embodiments of the system and method allow a user to gain a greater understanding of the data and to gain new insights into their data. Embodiments of the system and method also allow a user to interactively explore the problem and to navigate different views of data. Many different classifier training and evaluation experiments are run simultaneously and results are obtained. The results are aggregated and visualized across each of the experiments to determine and understand how each example is classified for each different classifier. These results then are summarized in a variety of ways to allow users to obtain a greater understanding of the data both in terms of the individual examples themselves and features associated with the data.
摘要翻译：一种用于同时运行多个机器学习模型的多模型数据挖掘系统和方法，用于理解和探索数据。该系统和方法的实施例允许用户更好地理解数据并获得对其数据的新见解。系统和方法的实施例还允许用户交互地探索问题并导航数据的不同视图。同时运行许多不同的分类器训练和评估实验，得到结果。结果在每个实验中进行聚合和可视化，以确定和理解每个示例如何分类给每个不同的分类器。然后以各种方式总结这些结果，以允许用户在各个示例本身和与数据相关的特征方面获得对数据的更多了解。

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