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    Tool for machine-learning data analysis
    13.
    发明授权
    Tool for machine-learning data analysis 有权

    公开(公告)号：US10956834B2

    公开(公告)日：2021-03-23

    申请号：US16707845

    申请日：2019-12-09

    Applicant: Splunk Inc.

    Inventor： Manish Sainani ,  Sergey Slepian ,  Iman Makaremi ,  Adam Jamison Oliner ,  Jacob Leverich ,  Di Lu

    IPC: G06N20/00 ,  H04L12/24 ,  G06N5/02

    Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.

    Concurrently forecasting multiple time series
    14.
    发明授权
    Concurrently forecasting multiple time series 有权

    公开(公告)号：US10726354B2

    公开(公告)日：2020-07-28

    申请号：US15143335

    申请日：2016-04-29

    Applicant: Splunk Inc.

    Inventor： Manish Sainani ,  Nghi Huu Nguyen ,  Zidong Yang

    IPC: G06N20/20 ,  G06N20/00 ,  G06F16/242 ,  G06F16/22 ,  G06F16/2458 ,  G06F16/248

    Abstract: Embodiments of the present invention are directed to facilitating concurrent forecasting associating with multiple time series data sets. In accordance with aspects of the present disclosure, a request to perform a predictive analysis in association with multiple time series data sets is received. Thereafter, the request is parsed to identify each of the time series data sets to use in predictive analysis. For each time series data set, an object is initiated to perform the predictive analysis for the corresponding time series data set. Generally, the predictive analysis predicts expected outcomes based on the corresponding time series data set. Each object is concurrently executed to generate expected outcomes associated with the corresponding time series data set, and the expected outcomes associated with each of the corresponding time series data sets are provided for display.

    Adaptive key performance indicator thresholds
    15.
    发明授权
    Adaptive key performance indicator thresholds 有权

    公开(公告)号：US10235638B2

    公开(公告)日：2019-03-19

    申请号：US14859236

    申请日：2015-09-18

    Applicant: Splunk Inc.

    Inventor： Sonal Maheshwari ,  Manish Sainani ,  Leonid Alekseyev ,  Alan Hardin ,  Jacob Barton Leverich ,  Adam Jamison Oliner ,  Brian Reyes ,  Alok Anant Bhide

    IPC: H04L29/08 ,  G06N99/00

    Abstract: Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs). Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.

    EVENT FORECASTING
    16.
    发明申请
    EVENT FORECASTING 审中-公开

    公开(公告)号：US20180218269A1

    公开(公告)日：2018-08-02

    申请号：US15419918

    申请日：2017-01-30

    Applicant: SPLUNK INC.

    Inventor： Adam Jamison Oliner ,  Aungon Nag Radon ,  Manwah Wong ,  Manish Sainani ,  Harsh Keswani

    IPC: G06N5/04 ,  G06N99/00 ,  G06F17/30

    CPC classification number: G06N5/04 ,  G06F16/2465 ,  G06F16/26 ,  G06N20/00

    Abstract: Embodiments of the present invention are directed to facilitating event forecasting. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to identify leading indicators that indicate a future occurrence of a target event, wherein the leading indicators occur during a search period of time the precedes a warning period of time, thereby providing time for an action to be performed prior to an occurrence of a predicted target event. At least one of the leading indicators is used to predict a target event. An event notification is provided indicating the prediction of the target event.

    Anomaly detection based on a predicted value
    20.
    发明授权
    Anomaly detection based on a predicted value 有权

    公开(公告)号：US11340774B1

    公开(公告)日：2022-05-24

    申请号：US16542774

    申请日：2019-08-16

    Applicant: Splunk Inc.

    Inventor： Manish Sainani ,  Adam Jamison Oliner ,  Jacob Barton Leverich ,  Leonid Alekseyev ,  Sonal Maheshwari

    IPC: G06F15/16 ,  G06F3/0488

    Abstract: Techniques are disclosed for anomaly detection based on a predicted value. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input.

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