Update docs/user_guides/fs/feature_monitoring/statistics_comparison.md

javierdlrm · robzor92 · web-flow · commit 9d2ca02a8691 · 2024-02-14T15:37:25.000+01:00
Co-authored-by: Robin Andersson &lt;robin.eric.andersson@gmail.com&gt;
diff --git a/docs/user_guides/fs/feature_monitoring/statistics_comparison.md b/docs/user_guides/fs/feature_monitoring/statistics_comparison.md
@@ -1,4 +1,4 @@
-Hopsworks feature monitoring allows you to monitor your feature data once they have been ingested into the Feature Store. You can define ==detection and reference windows== over your data for which Hopsworks will compute the statistics on a regular basis, compared them, and optionally trigger alerts when significant differences are detected. Statistics can be computed on all or a subset of feature values, and on one or more features simultaneously. Also, you can specify the criteria under which statistics will be compared and set thresholds used to classify feature values as anomalous.
+Hopsworks feature monitoring allows you to monitor your feature data once they have been ingested into the Feature Store. You can define ==detection and reference windows== over your data for which Hopsworks will compute the statistics on a regular basis, compare them, and optionally trigger alerts when significant differences are detected. Statistics can be computed on all or a subset of feature values, and on one or more features simultaneously. Also, you can specify the criteria under which statistics will be compared and set thresholds used to classify feature values as anomalous.
 
 Hopsworks stores both detection and reference statistics and enable you to visualise the temporal evolution of statistical metrics. 
 

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`1`		-Hopsworks feature monitoring allows you to monitor your feature data once they have been ingested into the Feature Store. You can define ==detection and reference windows== over your data for which Hopsworks will compute the statistics on a regular basis, compared them, and optionally trigger alerts when significant differences are detected. Statistics can be computed on all or a subset of feature values, and on one or more features simultaneously. Also, you can specify the criteria under which statistics will be compared and set thresholds used to classify feature values as anomalous.
	`1`	+Hopsworks feature monitoring allows you to monitor your feature data once they have been ingested into the Feature Store. You can define ==detection and reference windows== over your data for which Hopsworks will compute the statistics on a regular basis, compare them, and optionally trigger alerts when significant differences are detected. Statistics can be computed on all or a subset of feature values, and on one or more features simultaneously. Also, you can specify the criteria under which statistics will be compared and set thresholds used to classify feature values as anomalous.
`2`	`2`
`3`	`3`	`Hopsworks stores both detection and reference statistics and enable you to visualise the temporal evolution of statistical metrics.`
`4`	`4`