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Применить Всего найдено 6. Отображено 6.
06-12-2012 дата публикации

Systems And Methods For Clustering Time Series Data Based On Forecast Distributions

Номер: US20120310939A1
Автор: Taiyeong Lee, David Rawlins Duling, LEE TAIYEONG, DULING DAVID RAWLINS
Принадлежит: SAS Institute Inc

In accordance with the teachings described herein, systems and methods are provided for clustering time series based on forecast distributions. A method for clustering time series based on forecast distributions may include: receiving time series data relating to one or more aspects of a physical process; applying a forecasting model to the time series data to generate forecasted values and confidence intervals associated with the forecasted values, the confidence intervals being generated based on distribution information relating to the forecasted values; generating a distance matrix that identifies divergence in the forecasted values, the distance matrix being generated based the distribution information relating to the forecasted values; and performing a clustering operation on the plurality of forecasted values based on the distance matrix. The distance matrix may be generated using a symmetric Kullback-Leibler divergence algorithm.

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Номер записи: 1
17-06-2010 дата публикации

Computer-Implemented Systems And Methods For Variable Clustering In Large Data Sets

Номер: US20100153456A1
Автор: Taiyeong Lee, David Rawlins Duling, Dominique Joseph Latour, LEE TAIYEONG, DULING DAVID RAWLINS, LATOUR DOMINIQUE JOSEPH
Принадлежит:

Computer-implemented systems and methods are provided for creating a cluster structure from a data set containing input variables. Global clusters are created within a first stage, by computing a similarity matrix from the data set. A global cluster structure and sub-cluster structure are created within a second stage, where the global cluster structure and the sub-cluster structure are created using a latent variable clustering technique and the cluster structure output is generated by combining the created global cluster structure and the created sub-cluster structure.

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Номер записи: 2
23-10-2012 дата публикации

Constrained optimized binning for scorecards

Номер: US0008296224B2
Автор: Ivan Borges Oliveira, Manoj Keshavmurthi Chari, David Rawlins Duling, Susan Edwards Haller, Robert William Pratt, OLIVEIRA IVAN BORGES, CHARI MANOJ KESHAVMURTHI, DULING DAVID RAWLINS, HALLER SUSAN EDWARDS, PRATT ROBERT WILLIAM
Принадлежит: SAS Institute Inc., OLIVEIRA IVAN BORGES, CHARI MANOJ KESHAVMURTHI, DULING DAVID RAWLINS, HALLER SUSAN EDWARDS, PRATT ROBERT WILLIAM, SAS INST INC, SAS INSTITUTE INC.

Computer-implemented systems and methods are provided for generating bins for a scorecard. An approximate set of bins is generated by applying an optimization model to binning data. The optimization model includes an objective function, constraints, and surrogate weight of evidence metric(s). The approximated set of bins are then used in scorecard operations.

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Номер записи: 3
29-05-2012 дата публикации

Computer-implemented systems and methods for variable clustering in large data sets

Номер: US0008190612B2
Автор: Taiyeong Lee, David Rawlins Duling, Dominique Joseph Latour, LEE TAIYEONG, DULING DAVID RAWLINS, LATOUR DOMINIQUE JOSEPH
Принадлежит: SAS Institute Inc., LEE TAIYEONG, DULING DAVID RAWLINS, LATOUR DOMINIQUE JOSEPH, SAS INST INC, SAS INSTITUTE INC.

Computer-implemented systems and methods are provided for creating a cluster structure from a data set containing input variables. Global clusters are created within a first stage, by computing a similarity matrix from the data set. A global cluster structure and sub-cluster structure are created within a second stage, where the global cluster structure and the sub-cluster structure are created using a latent variable clustering technique and the cluster structure output is generated by combining the created global cluster structure and the created sub-cluster structure.

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Номер записи: 4
01-04-2010 дата публикации

Constrained Optimized Binning For Scorecards

Номер: US20100082469A1
Автор: Ivan Borges Oliveira, Manoj Keshavmurthi Chari, David Rawlins Duling, Susan Edwards Haller, Robert William Pratt, OLIVEIRA IVAN BORGES, CHARI MANOJ KESHAVMURTHI, DULING DAVID RAWLINS, HALLER SUSAN EDWARDS, PRATT ROBERT WILLIAM
Принадлежит: SAS Institute Inc.

Computer-implemented systems and methods are provided for generating bins for a scorecard. An approximate set of bins is generated by applying an optimization model to binning data. The optimization model includes an objective function, constraints, and surrogate weight of evidence metric(s). The approximated set of bins are then used in scorecard operations.

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Номер записи: 5
10-05-2016 дата публикации

Systems and methods for clustering time series data based on forecast distributions

Номер: US0009336493B2
Автор: Taiyeong Lee, David Rawlins Duling, LEE TAIYEONG, DULING DAVID RAWLINS
Принадлежит: SAS Institute Inc., LEE TAIYEONG, DULING DAVID RAWLINS, SAS INST INC, SAS INSTITUTE INC.

In accordance with the teachings described herein, systems and methods are provided for clustering time series based on forecast distributions. A method for clustering time series based on forecast distributions may include: receiving time series data relating to one or more aspects of a physical process; applying a forecasting model to the time series data to generate forecasted values and confidence intervals associated with the forecasted values, the confidence intervals being generated based on distribution information relating to the forecasted values; generating a distance matrix that identifies divergence in the forecasted values, the distance matrix being generated based the distribution information relating to the forecasted values; and performing a clustering operation on the plurality of forecasted values based on the distance matrix. The distance matrix may be generated using a symmetric Kullback-Leibler divergence algorithm.

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Номер записи: 6