DISTRIBUTED, MULTI-MODEL, SELF-LEARNING PLATFORM FOR MACHINE LEARNING
    1.
    发明申请
    DISTRIBUTED, MULTI-MODEL, SELF-LEARNING PLATFORM FOR MACHINE LEARNING 审中-公开
    分布式,多模式,自学习机器学习平台

    公开(公告)号:US20160132787A1

    公开(公告)日:2016-05-12

    申请号:US14598628

    申请日:2015-01-16

    IPC分类号: G06N99/00

    CPC分类号: G06N20/00

    摘要: A system is provided for multi-methodology, multi-user, self-optimizing Machine Learning as a Service for that automates and optimizes the model training process. The system uses a large-scale distributed architecture and is compatible with cloud services. The system uses a hybrid optimization technique to select between multiple machine learning approaches for a given dataset. The system can also use datasets to transferring knowledge of how one modeling methodology has previously worked over to a new problem.

    摘要翻译: 提供了一种用于多方法,多用户,自优化机器学习即服务的系统,用于自动化和优化模型训练过程。 该系统使用大规模分布式架构,与云服务兼容。 该系统使用混合优化技术在给定数据集的多机器学习方法之间进行选择。 该系统还可以使用数据集来传递关于一种建模方法如何以前对新问题的了解。

    Methods and Apparatus for Interactive Name Searching Techniques
    2.
    发明申请
    Methods and Apparatus for Interactive Name Searching Techniques 有权
    交互式名称搜索技术的方法和装置

    公开(公告)号:US20090070320A1

    公开(公告)日:2009-03-12

    申请号:US12119028

    申请日:2008-05-12

    IPC分类号: G06F17/30

    CPC分类号: G06N3/126 G06F17/30716

    摘要: Methods and apparatus include presenting an initial set of names to a user. The user selects a set of names from those presented. An Interactive Evolutionary Algorithm (IEA) extracts features of each selected name from a database of names and features to form a feature set. The IEA forms a set of match features that are chosen from the feature set according to a priority function and/or weighting of the features, either of which may vary in succeeding iterations. The IEA searches the database to obtain a candidate set of names, where each name has features matching the match features. One or more names is chosen from the candidate set and added into a presentation set of names. The IEA may repeat the formation of the match features, candidate set, and selection of one or more names from the candidate set until the new presentation set is complete.

    摘要翻译: 方法和装置包括向用户呈现一组初始名称。 用户从提供的名称中选择一组名称。 交互式进化算法(IEA)从名称和特征数据库中提取每个选定名称的特征,形成一个特征集。 IEA形成一组匹配特征,其根据优先级功能和/或特征的加权从特征集中选择,其中任一个可以在随后的迭代中变化。 IEA搜索数据库以获取候选名称集,其中每个名称具有匹配匹配特征的特征。 从候选集中选择一个或多个名称,并将其添加到名称的表示集中。 IEA可以重复形成匹配特征,候选集合以及从候选集合中选择一个或多个名称直到新的呈现集合完成。

    Methods and apparatus or interactive name searching techniques
    3.
    发明授权
    Methods and apparatus or interactive name searching techniques 有权
    方法和设备或交互式名称搜索技术

    公开(公告)号:US08725755B2

    公开(公告)日:2014-05-13

    申请号:US12119028

    申请日:2008-05-12

    IPC分类号: G06F17/30

    CPC分类号: G06N3/126 G06F17/30716

    摘要: Methods and apparatus include presenting an initial set of names to a user. The user selects a set of names from those presented. An Interactive Evolutionary Algorithm (IEA) extracts features of each selected name from a database of names and features to form a feature set. The IEA forms a set of match features that are chosen from the feature set according to a priority function and/or weighting of the features, either of which may vary in succeeding iterations. The IEA searches the database to obtain a candidate set of names, where each name has features matching the match features. One or more names is chosen from the candidate set and added into a presentation set of names. The IEA may repeat the formation of the match features, candidate set, and selection of one or more names from the candidate set until the new presentation set is complete.

    摘要翻译: 方法和装置包括向用户呈现一组初始名称。 用户从提供的名称中选择一组名称。 交互式进化算法(IEA)从名称和特征数据库中提取每个选定名称的特征,形成一个特征集。 IEA形成一组匹配特征,这些匹配特征根据优先级功能和/或特征的加权从特征集中选择,其中任一个可以在随后的迭代中变化。 IEA搜索数据库以获取候选名称集,其中每个名称具有匹配匹配特征的特征。 从候选集中选择一个或多个名称,并将其添加到名称的表示集中。 IEA可以重复形成匹配特征,候选集合以及从候选集合中选择一个或多个名称直到新的呈现集合完成。