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1. 发明授权

US08275723B2 System for providing data analysis services using a support vector machine for processing data received from a remote source 有权
标题翻译：用于使用支持向量机提供数据分析服务的系统，用于处理从远程源接收的数据
公开(公告)号：US08275723B2
公开(公告)日：2012-09-25
申请号：US12814431
申请日：2010-06-11
申请人： Stephen D. Barnhill , Isabelle Guyon , Jason Weston
发明人： Stephen D. Barnhill , Isabelle Guyon , Jason Weston
IPC分类号： G06F15/18 , G06N3/00 , G06N3/12
CPC分类号： G06K9/623 , G06F19/20 , G06F19/24 , G06K9/6228 , G06K9/6231 , G06K9/6256 , G06K9/6269 , G06N99/005 , G06Q10/0637 , G06Q20/10 , G06Q40/06 , G06Q50/22 , G06T7/0012 , Y02A90/22 , Y02A90/26
摘要： A network-based system is provided for performing data analysis services using a support vector machine for analyzing data received from a remote user connected to the network. The user transmits a data set to be analyzed and along with an account identifier that allows the analysis service provider to collect payment for the processing services. Once payment has been confirmed, the service provider's server transmits the analysis results to the remote user.
摘要翻译：提供了一种基于网络的系统，用于使用支持向量机执行数据分析服务，用于分析从连接到网络的远程用户接收的数据。用户发送要分析的数据集，以及允许分析服务提供商收集处理服务的支付的帐户标识符。付款确认后，服务提供商的服务器将分析结果发送给远程用户。

2. 发明授权

US08543519B2 System and method for remote melanoma screening 有权
标题翻译：远程黑素瘤筛查的系统和方法
公开(公告)号：US08543519B2
公开(公告)日：2013-09-24
申请号：US12975306
申请日：2010-12-21
申请人： Isabelle Guyon , Stephen D. Barnhill
发明人： Isabelle Guyon , Stephen D. Barnhill
IPC分类号： G06F15/18
CPC分类号： G06N99/005 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T7/62 , G06T7/66 , G06T7/68 , G06T2207/10024 , G06T2207/20081 , G06T2207/30088 , G16H50/20 , G16H50/30
摘要： A system and method are provided for diagnosing diseases or conditions from digital images taken by a remote user with a smart phone or a digital camera and transmitted to an image analysis server in communication with a distributed network. The image analysis server includes a trained learning machine for classification of the images. The user-provided image is pre-processed to extract dimensional, shape and color features then is processed using the trained learning machine to classify the image. The classification result is postprocessed to generate a risk score that is transmitted to the remote user. A database associated with the server may include referral information for geographically matching the remote user with a local physician. An optional operation includes collection of financial information to secure payment for analysis services.
摘要翻译：提供了一种用于通过智能电话或数字照相机从远程用户拍摄的数字图像诊断疾病或病症的系统和方法，并且传送到与分布式网络通信的图像分析服务器。图像分析服务器包括用于分类图像的训练学习机。用户提供的图像被预处理以提取尺寸，形状和颜色特征，然后使用训练学习机处理以对图像进行分类。分类结果进行后处理，以生成传送给远程用户的风险分数。与服务器相关联的数据库可以包括用于将远程用户与当地医师地理上匹配的引荐信息。可选操作包括收集财务信息以确保分析服务的支付。

3. 发明申请

US20120008838A1 SYSTEM AND METHOD FOR REMOTE MELANOMA SCREENING 有权
标题翻译：用于远程MELANOMA筛选的系统和方法
公开(公告)号：US20120008838A1
公开(公告)日：2012-01-12
申请号：US12975306
申请日：2010-12-21
申请人： Isabelle Guyon , Stephen D. Barnhill
发明人： Isabelle Guyon , Stephen D. Barnhill
IPC分类号： G06K9/00
CPC分类号： G06N99/005 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T7/62 , G06T7/66 , G06T7/68 , G06T2207/10024 , G06T2207/20081 , G06T2207/30088 , G16H50/20 , G16H50/30
摘要： A system and method are provided for diagnosing diseases or conditions from digital images taken by a remote user with a smart phone or a digital camera and transmitted to an image analysis server in communication with a distributed network. The image analysis server includes a trained learning machine for classification of the images. The user-provided image is pre-processed to extract dimensional, shape and color features then is processed using the trained learning machine to classify the image. The classification result is postprocessed to generate a risk score that is transmitted to the remote user. A database associated with the server may include referral information for geographically matching the remote user with a local physician. An optional operation includes collection of financial information to secure payment for analysis services.
摘要翻译：提供了一种系统和方法，用于通过智能电话或数字照相机从远程用户拍摄的数字图像中诊断疾病或病症，并传送到与分布式网络通信的图像分析服务器。图像分析服务器包括用于分类图像的训练学习机。用户提供的图像被预处理以提取尺寸，形状和颜色特征，然后使用训练学习机处理以对图像进行分类。分类结果进行后处理，以生成传送给远程用户的风险分数。与服务器相关联的数据库可以包括用于将远程用户与当地医师地理上匹配的引荐信息。可选操作包括收集财务信息以确保分析服务的支付。

4. 发明授权

US08095483B2 Support vector machine—recursive feature elimination (SVM-RFE) 有权
标题翻译：支持向量机递归特征消除（SVM-RFE）
公开(公告)号：US08095483B2
公开(公告)日：2012-01-10
申请号：US12957411
申请日：2010-12-01
申请人： Jason Weston , Isabelle Guyon
发明人： Jason Weston , Isabelle Guyon
IPC分类号： G06F15/18
CPC分类号： G06F19/24 , G06F19/20 , G06K9/6231
摘要： Identification of a determinative subset of features from within a group of features is performed by training a support vector machine using training samples with class labels to determine a value of each feature, where features are removed based on their the value. One or more features having the smallest values are removed and an updated kernel matrix is generated using the remaining features. The process is repeated until a predetermined number of features remain which are capable of accurately separating the data into different classes.
摘要翻译：通过使用具有类标签的训练样本来训练支持向量机来确定特征组中的特征的确定性子集来确定每个特征的值，其中基于其特征被去除。删除具有最小值的一个或多个特征，并且使用其余特征生成更新的内核矩阵。重复该过程，直到保持能够将数据精确地分离成不同类别的预定数量的特征。

5. 发明申请

US20100256988A1 SYSTEM FOR PROVIDING DATA ANALYSIS SERVICES USING A SUPPORT VECTOR MACHINE FOR PROCESSING DATA RECEIVED FROM A REMOTE SOURCE 有权
标题翻译：使用支持向量机提供数据分析服务的系统，用于处理从远程源获取的数据
公开(公告)号：US20100256988A1
公开(公告)日：2010-10-07
申请号：US12814431
申请日：2010-06-11
申请人： Stephen Barnhill , Isabelle Guyon , Jason Weston
发明人： Stephen Barnhill , Isabelle Guyon , Jason Weston
IPC分类号： G06Q40/00 , G06F15/18 , G06N5/02 , G06Q10/00 , G06Q50/00
CPC分类号： G06K9/623 , G06F19/20 , G06F19/24 , G06K9/6228 , G06K9/6231 , G06K9/6256 , G06K9/6269 , G06N99/005 , G06Q10/0637 , G06Q20/10 , G06Q40/06 , G06Q50/22 , G06T7/0012 , Y02A90/22 , Y02A90/26
摘要： A network-based system is provided for performing data analysis services using a support vector machine for analyzing data received from a remote user connected to the network. The user transmits a data set to be analyzed and along with an account identifier that allows the analysis service provider to collect payment for the processing services. Once payment has been confirmed, the service provider's server transmits the analysis results to the remote user.
摘要翻译：提供了一种基于网络的系统，用于使用支持向量机执行数据分析服务，用于分析从连接到网络的远程用户接收的数据。用户发送要分析的数据集，以及允许分析服务提供商收集处理服务的支付的帐户标识符。付款确认后，服务提供商的服务器将分析结果发送给远程用户。

6. 发明授权

US07797257B2 System for providing data analysis services using a support vector machine for processing data received from a remote source 失效
标题翻译：用于使用支持向量机提供数据分析服务的系统，用于处理从远程源接收的数据
公开(公告)号：US07797257B2
公开(公告)日：2010-09-14
申请号：US11926129
申请日：2007-10-29
申请人： Stephen Barnhill , Isabelle Guyon , Jason Weston
发明人： Stephen Barnhill , Isabelle Guyon , Jason Weston
IPC分类号： G06N3/00 , G06F15/18
CPC分类号： G06K9/623 , G06F19/20 , G06F19/24 , G06K9/6228 , G06K9/6231 , G06K9/6256 , G06K9/6269 , G06N99/005 , G06Q10/0637 , G06Q20/10 , G06Q40/06 , G06Q50/22 , G06T7/0012 , Y02A90/22 , Y02A90/26
摘要： A computer system for performing data analysis services using a support vector machine for analyzing data received from a remote source on a distributed network includes a server in communication with the distributed network for receiving a data set and a financial account identifier associated with the remote source. The server communicates over the distributed network with a financial institution to receive funds from a financial account identified by the financial account identifier. A processor receives one or more data sets from the remote source and pre-processes the data to enhance meaning within the data set. The pre-processed data is used to train and test a support vector machine for recognizing patterns within the data. Live data is processed using the trained and tested support vector machine to generate an output which is transmitted to the remote source after the server confirms that payment for the data processing service has been received.
摘要翻译：用于使用支持向量机执行数据分析服务的计算机系统用于分析从分布式网络上的远程源接收的数据，包括与分布式网络通信的服务器，用于接收与远程源相关联的数据集和财务帐户标识符。服务器通过分布式网络与金融机构进行通信，从金融账户标识符识别的金融账户接收资金。处理器从远程源接收一个或多个数据集，并且预处理数据以增强数据集内的含义。预处理数据用于训练和测试支持向量机，用于识别数据内的模式。使用经过训练和测试的支持向量机处理实时数据，以产生在服务器确认已经接收到数据处理服务的支付之后被发送到远程源的输出。

7. 发明申请

US20110106735A1 RECURSIVE FEATURE ELIMINATION METHOD USING SUPPORT VECTOR MACHINES 审中-公开
标题翻译：使用支持向量机的回归特征消除方法
公开(公告)号：US20110106735A1
公开(公告)日：2011-05-05
申请号：US12944197
申请日：2010-11-11
申请人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
发明人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
IPC分类号： G06F15/18
CPC分类号： G06K9/6231 , G06N20/00 , G06N20/10 , G16B25/00 , G16B40/00
摘要： Identification of a determinative subset of features from within a group of features is performed by training a support vector machine using training samples with class labels to determine a value of each feature, where features are removed based on their the value. One or more features having the smallest values are removed and an updated kernel matrix is generated using the remaining features. The process is repeated until a predetermined number of features remain which are capable of accurately separating the data into different classes. In some embodiments, features are eliminated by a ranking criterion based on a Lagrange multiplier corresponding to each training sample.
摘要翻译：通过使用具有类标签的训练样本来训练支持向量机来确定特征组中的特征的确定性子集来确定每个特征的值，其中基于其特征被去除。删除具有最小值的一个或多个特征，并且使用其余特征生成更新的内核矩阵。重复该过程，直到保持能够将数据精确地分离成不同类别的预定数量的特征。在一些实施例中，通过基于对应于每个训练样本的拉格朗日乘数的排序标准来消除特征。

8. 发明申请

US20050131847A1 Pre-processed feature ranking for a support vector machine 失效
标题翻译：支持向量机的预处理功能排名
公开(公告)号：US20050131847A1
公开(公告)日：2005-06-16
申请号：US10494876
申请日：2002-11-07
申请人： Jason Weston , Andre Elisseeff , Bernhard Scholkopf , Fernando Perez-Cruz , Isabelle Guyon
发明人： Jason Weston , Andre Elisseeff , Bernhard Scholkopf , Fernando Perez-Cruz , Isabelle Guyon
IPC分类号： G06F15/18 , G06G7/00 , G06K9/62
CPC分类号： G06K9/623 , G06K9/6269 , G06N99/005
摘要： Features are preprocessed (204) to minimize classification error in a Support Vector Machines (200) used to identify patterns in large databases. Pre-processing (204) is performed to constrain features used to train (210) the SVM learning machine. Live data (226) is collected and processed (232) with SVM.
摘要翻译：特征是预处理（204），以最小化用于识别大型数据库中的模式的支持向量机（200）中的分类错误。执行预处理（204）以约束用于训练（210）SVM学习机器的特征。使用SVM收集和处理实时数据（226）（232）。

9. 发明授权

US07805388B2 Method for feature selection in a support vector machine using feature ranking 失效
标题翻译：使用特征排序的支持向量机中特征选择的方法
公开(公告)号：US07805388B2
公开(公告)日：2010-09-28
申请号：US11928784
申请日：2007-10-30
申请人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
发明人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
IPC分类号： G06N7/00
CPC分类号： C12Q1/6883 , C12Q2600/112 , C12Q2600/158 , G06F19/20 , G06F19/24 , G06K9/6231 , G06K9/6269
摘要： In a pre-processing step prior to training a learning machine, pre-processing includes reducing the quantity of features to be processed using feature selection methods selected from the group consisting of recursive feature elimination (RFE), minimizing the number of non-zero parameters of the system (l0-norm minimization), evaluation of cost function to identify a subset of features that are compatible with constraints imposed by the learning set, unbalanced correlation score, transductive feature selection and single feature using margin-based ranking. The features remaining after feature selection are then used to train a learning machine for purposes of pattern classification, regression, clustering and/or novelty detection.
摘要翻译：在训练学习机之前的预处理步骤中，预处理包括使用从递归特征消除（RFE）中选出的特征选择方法来减少要处理的特征量的数量，使非零参数的数量最小化（10-norm minimization），评估成本函数以识别与由学习集施加的约束兼容的特征的子集，不平衡相关得分，转换特征选择和使用基于边缘的排名的单个特征。然后，特征选择之后剩余的特征用于训练学习机，用于模式分类，回归，聚类和/或新颖性检测。

10. 发明授权

US07475048B2 Pre-processed feature ranking for a support vector machine 失效
标题翻译：支持向量机的预处理功能排名
公开(公告)号：US07475048B2
公开(公告)日：2009-01-06
申请号：US10494876
申请日：2002-11-07
申请人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
发明人： Jason Weston , André Elisseeff , Bernhard Schölkopf , Fernando Perez-Cruz , Isabelle Guyon
IPC分类号： G06F15/18
CPC分类号： G06K9/623 , G06K9/6269 , G06N99/005
摘要： A computer-implemented method is provided for ranking features within a large dataset containing a large number of features according to each feature's ability to separate data into classes. For each feature, a support vector machine separates the dataset into two classes and determines the margins between extremal points in the two classes. The margins for all of the features are compared and the features are ranked based upon the size of the margin, with the highest ranked features corresponding to the largest margins. A subset of features for classifying the dataset is selected from a group of the highest ranked features. In one embodiment, the method is used to identify the best genes for disease prediction and diagnosis using gene expression data from micro-arrays.
摘要翻译：提供了一种计算机实现的方法，用于根据每个特征将数据分离成类的能力，对包含大量特征的大型数据集中的特征进行排名。对于每个特征，支持向量机将数据集分为两类，并确定两类极值点之间的边距。比较所有功能的边距，并根据边距的大小对特征进行排名，排名最高的功能对应于最大的边距。从一组最高排名的特征中选择用于分类数据集的特征的子集。在一个实施方案中，该方法用于使用来自微阵列的基因表达数据鉴定用于疾病预测和诊断的最佳基因。

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