1,595
17
Essay, 2 pages (250 words)

Elasticsearch x-pack machine learning

Statistical ModelMathematical description of data over time4 Keys of Anomaly DetectionFeature selection
Loading Existing Data
Period Detection
Empirical Sorting ONELASTICSEARCH X-PACK MACHINE LEARNING SPECIFICALLY FOR YOUFOR ONLY$13. 90/PAGEOrder NowFeature selectionCreating detection rules off of your data pointsPeriod DetectionChoosing what frequency of time is meaningful to the data. Empirical scoringDefining which automatically detected anomalies are important. Bucket SpansParameter range that divides data into batches for processing (usually time)Analysis functionFunction that is applied to the bucket span, count, sum, metric etc. Machine Learning JobRunning of the analysis function(s) over the determined bucket spansDetectorMultiple analysis functions with a shared bucket span. Event/Data FeedPushes data into a job.
May be a query.
Can be range based or live.
Can be run on pre-aggregated data. InfluencerAttribute that has an influence on the data, something that has contributed to the anomalyAnomaly ScoreCombination of individual item scoring and bucket scoringIndividual item scoringHow anomalous an event is to a baseline.
Based on past behaviorBucket scoringComparing an anomaly to other readings in the bucket.
Aggregate score across all detectors for the job
Only one score per bucket. Partition fieldsFields with a low enough cardinality to run a machine learning job over each distinct value.
Advanced job parameter that duplicates the job over values of the field and performs analysis in parallel. Individual Anomaly DetectionComparison of a behavior to it’s own historical behaviorPopulation Anomaly DetectionComparison of a behavior to the behavior of other members of a population. Over FieldsAdvanced job parameter used to perform population anomaly detection. By fieldsAdvanced job parameter used to perform individual anomaly detection. Jobs are performed in serial, then categorized BY field. By field anomaly scoreUses total anomaly ratio for all by field valuesPartition field anomaly scoreUses individual anomaly ratio for all partition field values

Thank's for Your Vote!
Elasticsearch x-pack machine learning. Page 1
Elasticsearch x-pack machine learning. Page 2
Elasticsearch x-pack machine learning. Page 3

This work, titled "Elasticsearch x-pack machine learning" was written and willingly shared by a fellow student. This sample can be utilized as a research and reference resource to aid in the writing of your own work. Any use of the work that does not include an appropriate citation is banned.

If you are the owner of this work and don’t want it to be published on AssignBuster, request its removal.

Request Removal
Cite this Essay

References

AssignBuster. (2022) 'Elasticsearch x-pack machine learning'. 2 October.

Reference

AssignBuster. (2022, October 2). Elasticsearch x-pack machine learning. Retrieved from https://assignbuster.com/elasticsearch-x-pack-machine-learning/

References

AssignBuster. 2022. "Elasticsearch x-pack machine learning." October 2, 2022. https://assignbuster.com/elasticsearch-x-pack-machine-learning/.

1. AssignBuster. "Elasticsearch x-pack machine learning." October 2, 2022. https://assignbuster.com/elasticsearch-x-pack-machine-learning/.


Bibliography


AssignBuster. "Elasticsearch x-pack machine learning." October 2, 2022. https://assignbuster.com/elasticsearch-x-pack-machine-learning/.

Work Cited

"Elasticsearch x-pack machine learning." AssignBuster, 2 Oct. 2022, assignbuster.com/elasticsearch-x-pack-machine-learning/.

Get in Touch

Please, let us know if you have any ideas on improving Elasticsearch x-pack machine learning, or our service. We will be happy to hear what you think: [email protected]