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    Facilitating alerts for predicted conditions
    11.
    发明授权
    Facilitating alerts for predicted conditions 有权

    公开(公告)号：US11593443B1

    公开(公告)日：2023-02-28

    申请号：US17449545

    申请日：2021-09-30

    Applicant: SPLUNK INC.

    Inventor： Iman Makaremi ,  Gyanendra Rana ,  Iryna Vogler-Ivashchanka ,  Adam Oliner ,  Harsh Keswani ,  Manish Sainani ,  Alexander Kim

    IPC: H04L41/069 ,  H04L67/141 ,  H04L41/0686 ,  G06F16/951 ,  G06F16/2458 ,  G06F40/30 ,  H04L67/01

    Abstract: Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of an automatic data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive the disparate data and ingest certain of the data as measurement entries of a DIQS metrics datastore that is searchable for DIQS query processing. The DIQS may receive search queries to process against the received and ingested data via an exposed network interface. In one example embodiment, a query building component conducts a user interface using a network attached client device. The query building component may elicit search criteria via the user interface using a natural language interface, construct a proper query therefrom, and present new information based on results returned from the DIQS.

    Facilitating metric forecasting via a graphical user interface
    12.
    发明授权
    Facilitating metric forecasting via a graphical user interface 有权

    公开(公告)号：US11188600B2

    公开(公告)日：2021-11-30

    申请号：US16904168

    申请日：2020-06-17

    Applicant: SPLUNK Inc.

    Inventor： Iman Makaremi ,  Gyanendra Rana ,  Iryna Vogler-Ivashchanka ,  Adam Oliner ,  Harsh Keswani ,  Manish Sainani ,  Alexander Kim

    IPC: G06F16/951 ,  H04L12/24 ,  H04L29/06 ,  H04L29/08 ,  G06F16/2458 ,  G06F40/30

    Abstract: Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of an automatic data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive the disparate data and ingest certain of the data as measurement entries of a DIQS metrics datastore that is searchable for DIQS query processing. The DIQS may receive search queries to process against the received and ingested data via an exposed network interface. In one example embodiment, a query building component conducts a user interface using a network attached client device. The query building component may elicit search criteria via the user interface using a natural language interface, construct a proper query therefrom, and present new information based on results returned from the DIQS.

    Automated data preprocessing for machine learning
    14.
    发明授权
    Automated data preprocessing for machine learning 有权

    公开(公告)号：US10817757B2

    公开(公告)日：2020-10-27

    申请号：US15665224

    申请日：2017-07-31

    Applicant: Splunk Inc.

    Inventor： Manish Sainani ,  Sergey Slepian ,  Di Lu ,  Adam Oliner ,  Jacob Leverich ,  Iryna Vogler-Ivashchanka ,  Iman Makaremi

    IPC: G06F7/00 ,  G06K9/62 ,  G06K9/00 ,  G06N20/00 ,  G06F16/2458 ,  G06N5/02 ,  G06F9/455

    Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.

    Generating machine learning-based outlier detection models using timestamped event data
    16.
    发明授权
    Generating machine learning-based outlier detection models using timestamped event data 有权

    公开(公告)号：US12014255B1

    公开(公告)日：2024-06-18

    申请号：US18334996

    申请日：2023-06-14

    Applicant: Splunk Inc.

    Inventor： Iryna Vogler-Ivashchanka ,  Iman Makaremi

    IPC: G06N20/00 ,  G06F16/9038 ,  G06F17/18

    CPC classification number: G06N20/00 ,  G06F16/9038 ,  G06F17/18

    Abstract: Techniques are described for providing a machine learning (ML) data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” One such model is an outlier detection model to assist in the monitoring of computer network traffic and computer performance. For example, the ML data analytics application may generate an outlier detection model using user-identified data from a data source and parameter information. The generates outlier detection model can include distribution functions of distribution types selected from a plurality of distribution types by a distribution fitting algorithm.

    Visualizing outliers from timestamped event data using machine learning-based models
    18.
    发明授权
    Visualizing outliers from timestamped event data using machine learning-based models 有权

    公开(公告)号：US11720824B1

    公开(公告)日：2023-08-08

    申请号：US17969538

    申请日：2022-10-19

    Applicant: Splunk Inc.

    Inventor： Iryna Vogler-Ivashchanka ,  Iman Makaremi

    IPC: G06N20/00 ,  G06F16/9038 ,  G06F17/18

    CPC classification number: G06N20/00 ,  G06F16/9038 ,  G06F17/18

    Abstract: Techniques are described for providing a machine learning (ML) data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” One such model is an outlier detection model to assist in the monitoring of computer network traffic and computer performance. For example, the ML data analytics application may generate an outlier detection model using user-identified data from a data source and parameter information. The generates outlier detection model can include distribution functions of distribution types selected from a plurality of distribution types by a distribution fitting algorithm.

    Guided workflows for machine learning-based data analyses
    19.
    发明授权
    Guided workflows for machine learning-based data analyses 有权

    公开(公告)号：US11574242B1

    公开(公告)日：2023-02-07

    申请号：US16399964

    申请日：2019-04-30

    Applicant: Splunk Inc.

    Inventor： Cory Eugene Burke ,  Gyanendra Rana ,  Sergey Slepian ,  Andrew Stein ,  Iryna Vogler-Ivashchanka

    IPC: G06F7/02 ,  G06F16/00 ,  G06N20/00 ,  G06F3/048 ,  G06F16/248 ,  G06F16/2458

    Abstract: Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.

    Machine learning-based data analyses for outlier detection
    20.
    发明授权
    Machine learning-based data analyses for outlier detection 有权

    公开(公告)号：US11537942B1

    公开(公告)日：2022-12-27

    申请号：US16528478

    申请日：2019-07-31

    Applicant: Splunk Inc.

    Inventor： Iryna Vogler-Ivashchanka ,  Iman Makaremi

    IPC: G06N20/00 ,  G06F16/9038 ,  G06F17/18

    Abstract: Techniques are described for providing a machine learning (ML) data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” One such model is an outlier detection model to assist in the monitoring of computer network traffic and computer performance. For example, the ML data analytics application may generate an outlier detection model using user-identified data from a data source and parameter information. The generates outlier detection model can include distribution functions of distribution types selected from a plurality of distribution types by a distribution fitting algorithm.

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