-
公开(公告)号：US20190377655A1
公开(公告)日：2019-12-12
申请号：US16433136
申请日：2019-06-06
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi
Abstract: Metadata received from each worker computing device describes EDF estimates for samples of marginal variables stored on each respective worker computing device. Combinations of the EDF estimates are enumerated and assigned to each worker computing device based on the metadata. A request to compute outcome expectation measure values for an outcome expectation measure is initiated to each worker computing device based on the assigned combinations. The outcome expectation measure values computed by each worker computing device are received from each respective worker computing device. The received outcome expectation measure values are accumulated for the outcome expectation measure. A mean value and a standard deviation value are computed for the outcome expectation measure from the accumulated, received outcome expectation measure values. The computed mean and standard deviation values for the outcome expectation measure are output to represent an expected outcome based on the marginal variables.
-
公开(公告)号：US10019411B2
公开(公告)日：2018-07-10
申请号：US14626187
申请日：2015-02-19
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described. An apparatus may comprise a configuration component, perturbation component, sample generation controller, an aggregation component, a distribution fitting component, and statistics generation component. The configuration component may be operative to receive a compound model specification and candidate distribution definition. The perturbation component may be operative to generate a plurality of models from the compound model specification. The sample generation controller may be operative to initiate the generation of a plurality of compound model samples from each of the plurality of models. The distribution fitting component may generate parameter values for the candidate distribution definition based on the compound model samples. The statistics generation component may generate approximated aggregate statistics. Other embodiments are described and claimed.
-
公开(公告)号：US10325008B2
公开(公告)日：2019-06-18
申请号：US15805774
申请日：2017-11-07
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
Abstract: Techniques for estimated compound probability distribution are described herein. Embodiments may include receiving a compound model specification comprising a frequency model and a severity model, the compound model specification including a model error comprising a frequency model error and a severity model error, and determining a number of frequency models and severity models to generate based on the received number of models to generate. Embodiments include generating a plurality of frequency models through perturbation of the frequency model according to the frequency model error, and generating a plurality of severity models through perturbation of the severity model according to the severity model error. Further, embodiments include dividing generation of a plurality of compound model samples among a plurality of distributed worker nodes, and receiving the plurality of compound model samples from the distributed worker nodes, and generating aggregate statistics from the plurality of compound model samples.
-
公开(公告)号：US10664555B2
公开(公告)日：2020-05-26
申请号：US16433192
申请日：2019-06-06
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi
IPC: G06F17/18 , G06F9/54 , G06F11/34 , G06N7/00 , G06F16/242
Abstract: A computing device provides distributed estimation of an empirical distribution function. A boundary cumulative distribution function (CDF) value is defined at a start of each region of a plurality of regions. An accuracy value is defined for each region. (a) First equal proportion bins are computed for a first sample of a first marginal variable using the defined boundary CDF value for each region. (b) Second equal proportion bins are computed for the first sample of the first marginal variable within each region based on the defined accuracy value for each region. (c) The computed second equal proportion bins are added as an empirical distribution function (EDF) for the first marginal variable. (d) (a) to (c) are repeated for each remaining sample of the first marginal variable. (e) (a) to (d) are repeated with each remaining marginal variable of a plurality of marginal variables as the first marginal variable.
-
公开(公告)号：US10565085B2
公开(公告)日：2020-02-18
申请号：US16433136
申请日：2019-06-06
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi
Abstract: Metadata received from each worker computing device describes EDF estimates for samples of marginal variables stored on each respective worker computing device. Combinations of the EDF estimates are enumerated and assigned to each worker computing device based on the metadata. A request to compute outcome expectation measure values for an outcome expectation measure is initiated to each worker computing device based on the assigned combinations. The outcome expectation measure values computed by each worker computing device are received from each respective worker computing device. The received outcome expectation measure values are accumulated for the outcome expectation measure. A mean value and a standard deviation value are computed for the outcome expectation measure from the accumulated, received outcome expectation measure values. The computed mean and standard deviation values for the outcome expectation measure are output to represent an expected outcome based on the marginal variables.
-
Patent Agency Ranking
公开(公告)号：US09665669B2
公开(公告)日：2017-05-30
申请号：US15197691
申请日：2016-06-29
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described. An apparatus comprising a configuration component, perturbation component, sample generation controller, an aggregation component, a distribution fitting component, and statistics generation component. The configuration component operative to receive a compound model specification and candidate distribution definition. The perturbation component operative to generate a plurality of models from the compound model specification. The sample generation controller operative to initiate the generation of a plurality of compound model samples from each of the plurality of models. The distribution fitting component to generate parameter values for the candidate distribution definition based on the compound model samples. The statistics generation component to generate approximated aggregate statistics.
-
公开(公告)号：US20190377774A1
公开(公告)日：2019-12-12
申请号：US16433192
申请日：2019-06-06
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi
IPC: G06F17/18
Abstract: A computing device provides distributed estimation of an empirical distribution function. A boundary cumulative distribution function (CDF) value is defined at a start of each region of a plurality of regions. An accuracy value is defined for each region. (a) First equal proportion bins are computed for a first sample of a first marginal variable using the defined boundary CDF value for each region. (b) Second equal proportion bins are computed for the first sample of the first marginal variable within each region based on the defined accuracy value for each region. (c) The computed second equal proportion bins are added as an empirical distribution function (EDF) for the first marginal variable. (d) (a) to (c) are repeated for each remaining sample of the first marginal variable. (e) (a) to (d) are repeated with each remaining marginal variable of a plurality of marginal variables as the first marginal variable.
-
公开(公告)号：US09928320B2
公开(公告)日：2018-03-27
申请号：US15485577
申请日：2017-04-12
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described herein. Embodiments may include receiving, at a master node of a distributed system, a compound model specification comprising frequency models, severity models, and one or more adjustment functions, wherein at least one model of the frequency models and the severity models depend on one or more regressor and distributing the compound model specification to worker nodes of the distributed system, each of the worker nodes to at least generate a portion of samples for use in predicting compound distribution model estimates. Embodiments may also include predicting the compound distribution model estimates based on the sample portions of aggregate values and adjusted aggregate values.
-
公开(公告)号：US12282753B1
公开(公告)日：2025-04-22
申请号：US18762480
申请日：2024-07-02
Applicant: SAS Institute Inc.
Inventor： Iman Vasheghani Farahani , Mahesh V. Joshi , Phillip M. Helmkamp , Rajib Nath , Vilochan Suresh Muley , Javier Delgado , Michele Angelo Trovero
IPC: G06F8/34 , G06F3/0482 , G06F3/0486 , G06F8/41 , G06F9/54 , G06F16/25 , G06F16/38 , G06F40/30 , H04L65/1101 , H04L67/01
Abstract: In one example, a computer system can generate a graphical user interface (GUI) for forecasting software including a drag-and-drop canvas with a set of rearrangeable nodes defining a forecasting pipeline. The computer system can detect a user interaction for attaching an external-language execution node to the pipeline, which can be used to insert custom code defined using an external programming language. The computer system can receive the custom code. The computer system can receive a user input to initiate execution of the pipeline. The computer system can generate wrapped custom code by augmenting the custom code with additional program code including shared variables. The computer system can provide the wrapped custom code to a set of execution threads configured to execute the wrapped custom code as part of the pipeline to generate one or more forecasts. The computer system can output the forecasts in the GUI.
-
公开(公告)号：US20250117192A1
公开(公告)日：2025-04-10
申请号：US18762480
申请日：2024-07-02
Applicant: SAS Institute Inc.
Inventor： Iman Vasheghani Farahani , Mahesh V. Joshi , Phillip M. Helmkamp , Rajib Nath , Vilochan Suresh Muley , Javier Delgado , Michele Angelo Trovero
IPC: G06F8/34 , G06F3/0486 , G06F8/41
Abstract: In one example, a computer system can generate a graphical user interface (GUI) for forecasting software including a drag-and-drop canvas with a set of rearrangeable nodes defining a forecasting pipeline. The computer system can detect a user interaction for attaching an external-language execution node to the pipeline, which can be used to insert custom code defined using an external programming language. The computer system can receive the custom code. The computer system can receive a user input to initiate execution of the pipeline. The computer system can generate wrapped custom code by augmenting the custom code with additional program code including shared variables. The computer system can provide the wrapped custom code to a set of execution threads configured to execute the wrapped custom code as part of the pipeline to generate one or more forecasts. The computer system can output the forecasts in the GUI.
-
-
-
-
-
-
-
-
-
Search Results
12
records
(took 0.015 seconds)
