Run diagnostic statistics

Understanding the performance of your experiments can involve analyzing many outputs and results. It’s often useful to see key metrics at a glance across all your runs, to allow you to quickly identify which experiments are worth investigating further.

Domino’s diagnostic statistics functionality allows you to do just that.

To use this feature, write a file named dominostats.json to the root of your project directory. Use keys in this JSON file to identify the outputs you're interested in, and then add the corresponding values.

 

Here is an example in R:

diagnostics = list("R^2" = 0.99, "p-value" = 0.05, "sse" = 10.49)
library(jsonlite)
fileConn<-file("dominostats.json")
writeLines(toJSON(diagnostics), fileConn)
close(fileConn)

And in Python:

import json
with open('dominostats.json', 'w') as f:
    f.write(json.dumps({"R^2": 0.99, "p-value": 0.05, "sse": 10.49}))

 

If Domino detects this file, it will parse the values out and show them as columns on the Jobs dashboard. Also, Job comparison reports will show these statistics rendered in a table as well to make it even easier to compare their performance.

 

Note

The dominostats.json file is deleted before each run automatically by Domino. Therefore, past dominostats.json files will not pollute new Jobs on your Jobs dashboard.

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