I am looking for a way to build a confusion matrix for image detection results (machine learning domain). I already uploaded my data to ElasticSearch and built index patterns for it. I tried different existing visualization templates, but all of them are not pretty good.
Could anyone explain how to build classic confusion matrix with Kibana ( columns and rows should be named as detection classes, numbers in cells = number of detections or number of confusions, colourful cells by its values)
Hi, I think the most general answer to your question is that you should be able to use the Heat Map visualization for this in Kibana. You will need to provide aggregations to determine the columns and rows, most commonly it will be the Terms aggregation, and an aggregation to determine the cell value like Avg.
It sounds like you aren't using the Elastic Machine Learning features, which also offer a built-in confusion matrix visualization for our models.
Finally, if you aren't able to use the heat map visualization for some reason, then your only alternative is to build the visualization manually using Vega. Vega is the visualization we offer when you need something beyond what Kibana offers by default.
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