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    Guided workflows for machine learning-based data analyses
    1.
    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.

    Tool for machine-learning data analysis
    6.
    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.

    AUTOMATIC GENERATION OF DATA ANALYSIS QUERIES
    8.
    发明申请
    AUTOMATIC GENERATION OF DATA ANALYSIS QUERIES 有权

    公开(公告)号：US20210192395A1

    公开(公告)日：2021-06-24

    申请号：US17190751

    申请日：2021-03-03

    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.

    Automated data preprocessing for machine learning
    10.
    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.

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