Hey, is there any way to improve the accuracy of my ML model? What parameters need to be tuned in order to increase its accuracy?
In general, the model gets more accurate by feeding it more historical data. That's the methodology of unsupervised learning. Of course, you can influence what gets modeled via filtered queries, choice of bucket_span, implementation of Custom Rules, etc.
Was this just a generic question or do you have some specific situation in which you believe the model that you are seeing isn't as accurate as you hope?
As you can see here, the lower and upper bounds for the data is irregular. I want my model to have the lower and upper bounds to be as accurate as possible?
Also, can you suggest me a blog which explains the advanced configuration for creating a ML job? I'm just not clear about it
Your model is actually quite accurate until you have the anomalies seen on 2019-06-16. That extended period of time has made the model have a different shape thereafter, but the model will recover after a few more days pass by.
Keep in mind that you only had about 15 days before these drastic anomalies occurred. If you had 100+ days, for example, the impact of those anomalies on the model would have been less.
If those anomalies were part of a known or planned outage, you could have avoided this situation by defining a Scheduled Event under Settings->Calendar
A nice article that explains the ins-and-outs of the Advanced Job can be found here:
I especially like how he created a visual map of how the configuration setup works:
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If you are interested in learning more about ML you can also look up this book:
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