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1. 发明授权

US09495775B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US09495775B2
公开(公告)日：2016-11-15
申请号：US10955738
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06T11/20 , G06F17/30
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

2. 发明授权

US07953738B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US07953738B2
公开(公告)日：2011-05-31
申请号：US10955585
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06F17/30
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

3. 发明授权

US07342582B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US07342582B2
公开(公告)日：2008-03-11
申请号：US10954743
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06T11/20
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

4. 发明授权

US07028036B2 System and method for visualization of continuous attribute values 失效
标题翻译：连续属性值可视化的系统和方法
公开(公告)号：US07028036B2
公开(公告)日：2006-04-11
申请号：US10185081
申请日：2002-06-28
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06F17/00 , G09G5/22
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

5. 发明授权

US07124054B2 System and method for mining model accuracy display 有权
标题翻译：挖掘模型精度显示的系统和方法
公开(公告)号：US07124054B2
公开(公告)日：2006-10-17
申请号：US10186052
申请日：2002-06-28
申请人： Pyungchul Kim , Zhaohui Tang , David Earl Heckerman , Scott Conrad Oveson
发明人： Pyungchul Kim , Zhaohui Tang , David Earl Heckerman , Scott Conrad Oveson
IPC分类号： G06E1/00
CPC分类号： G06F17/18 , G06F17/30539
摘要： Systems and methods are provided for producing displays of the accuracy of data mining or statistical models that produce associative predictions. For all cases in a testing data set, the model makes predictions and provides associated probabilities. The cases are sorted by their probability of making accurate predictions and a graph is made of the accuracy of the model over various subsets containing the highest probability cases as evaluated by the model. Where a number of probabilities are presented for the predictions in a basket of predictions, those probabilities are combined to yield a probability score for the entire basket. Additionally, the accuracy of a model over different basket sizes may be graphed. The accuracy graph may also be produced for any models making a prediction, by graphing the probability of making accurate predictions and a graph made of the accuracy of the model over various subsets of the data containing the highest probability cases.
摘要翻译：提供系统和方法用于产生数据挖掘的准确性的显示或产生关联预测的统计模型。对于测试数据集中的所有情况，模型进行预测并提供相关概率。这些案例按照准确预测的概率进行排序，并且通过模型评估，对包含最高概率案例的各种子集的模型精度进行了图形化。在对一篮子预测中的预测提出若干概率的情况下，将这些概率组合起来以产生整个篮子的概率得分。此外，可以绘制不同篮子尺寸的模型的精度。也可以通过绘制准确预测的概率和通过包含最高概率情况的数据的各种子集对模型的精度进行绘制的图形来产生准确度图。

6. 发明授权

US06807537B1 Mixtures of Bayesian networks 失效
标题翻译：贝叶斯网络的混合
公开(公告)号：US06807537B1
公开(公告)日：2004-10-19
申请号：US08985114
申请日：1997-12-04
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

7. 发明授权

US06408290B1 Mixtures of bayesian networks with decision graphs 失效
标题翻译：贝叶斯网络与决策图的混合
公开(公告)号：US06408290B1
公开(公告)日：2002-06-18
申请号：US09220200
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

8. 发明授权

US06496816B1 Collaborative filtering with mixtures of bayesian networks 有权
标题翻译：使用贝叶斯网络混合进行协同过滤
公开(公告)号：US06496816B1
公开(公告)日：2002-12-17
申请号：US09220199
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

9. 发明授权

US06345265B1 Clustering with mixtures of bayesian networks 有权
标题翻译：聚类与贝叶斯网络的混合
公开(公告)号：US06345265B1
公开(公告)日：2002-02-05
申请号：US09220192
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： The invention employs mixtures of Bayesian networks to perform clustering. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. The invention determines membership of an individual case in a cluster based upon a set of data of plural individual cases by first learning the structure and parameters of an MBN given that data and then using the MBN to compute the probability of each HSBN generating the data of the individual case.
摘要翻译：本发明采用贝叶斯网络的混合来执行聚类。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。本发明通过首先学习给定该数据的MBN的结构和参数，然后使用MBN来计算生成数据的每个HSBN的概率，从而基于多个单独情况的一组数据来确定集群中的个别情况的成员资格个别情况。

10. 发明授权

US06336108B1 Speech recognition with mixtures of bayesian networks 有权
标题翻译：语音识别与贝叶斯网络的混合
公开(公告)号：US06336108B1
公开(公告)日：2002-01-01
申请号：US09220197
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman , Fileno A. Alleva , Mei-Yuh Hwang
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman , Fileno A. Alleva , Mei-Yuh Hwang
IPC分类号： G06F1518
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： The invention performs speech recognition using an array of mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of those states. In accordance with the invention, the MBNs encode the probabilities of observing the sets of acoustic observations given the utterance of a respective one of said parts of speech. Each of the HSBNs encodes the probabilities of observing the sets of acoustic observations given the utterance of a respective one of the parts of speech and given a hidden common variable being in a particular state. Each HSBN has nodes corresponding to the elements of the acoustic observations. These nodes store probability parameters corresponding to the probabilities with causal links representing dependencies between ones of said nodes.
摘要翻译：本发明使用贝叶斯网络混合的阵列来执行语音识别。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于共同外部隐藏变量的状态数，并且每个HSBN在假设下共同的外部隐藏变量处于相应的一个状态的假设下对世界进行建模。根据本发明，MBN编码了考虑到所述话音部分中的相应一个的话语来观察声学观测组的概率。每个HSBN编码观察给定语音相应的一个语音的发音并给出隐藏的公共变量处于特定状态的声学观察组的概率。每个HSBN具有对应于声学观测元素的节点。这些节点存储对应于概率的概率参数，其中因果链接表示所述节点之间的依赖关系。

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