Machine learning-based data analyses for outlier detection
AssigneeSplunk Inc.
InventorsIryna Vogler-Ivashchanka, Iman Makaremi
Life of this patent
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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.
Claims30
A computer-implemented method comprising:
- causing display of a first user interface component, the first user interface component enabling user identification of data to be used to generate an outlier detection model using an outlier detection algorithm;
- obtaining the data from a data source;
- causing display of a second user interface component, the second user interface component enabling user indication of parameter information related to the outlier detection model;
- generating the outlier detection model based on the data from the data source and the parameter information related to the outlier detection model;
- and
- causing display of a third user interface component, the third user interface component including information about the outlier detection model.
A non-transitory computer-readable storage medium storing instructions which, when executed by one or more processors, cause performance of operations comprising:
- causing display of a first user interface component, the first user interface component enabling user identification of data to be used to generate an outlier detection model using an outlier detection algorithm;
- obtaining the data from a data source;
- causing display of a second user interface component, the second user interface component enabling user indication of parameter information related to the outlier detection model;
- generating the outlier detection model based on the data from the data source and the parameter information related to the outlier detection model;
- and
- causing display of a third user interface component, the third user interface component including information about the outlier detection model.
An apparatus, comprising:
- one or more processors;
- a non-transitory computer-readable storage medium storing instructions which, when executed by the one or more processors, causes the apparatus to:
- cause display of a first user interface component, the first user interface component enabling user identification of data to be used to generate an outlier detection model using an outlier detection algorithm;
- obtain the data from a data source;
- causing display of a second user interface component, the second user interface component enabling user indication of parameter information related to the outlier detection model;
- generate the outlier detection model based on the data from the data source and the parameter information related to the outlier detection model;
- and
- cause display of a third user interface component, the third user interface component including information about the outlier detection model.
Dependencies are inferred from the claim text.