r/MLQuestions • u/Alarmed-Payment-213 • 6d ago

Beginner question 👶 CPU forecasting using ML

Hello everyone. ML beginner here. I have the basic understanding of ML and have been given a project to create a model through which we can predict cpu metrics so that we can proactively monitor cpu spikes before it creates an incident. I’ve been using Claude to help me out here and it suggests to use XGBoost for this. But the accuracy is not up to the mark. Can anyone help me out here if you have worked on similar projects. Thanks for the help in advance

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u/National-Stick-4082 6d ago

I feel xgboost is just fine. Xgboost is dependent on the features you give it and the label. Trees are powerful and the task is simple enough that throwing a 100m parameter attention model at it is over engineering to the maximum.

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u/PradeepAIStrategist 5d ago

The most prominent issue with the data you are dealing is non seasonal occurrences of sudden spikes. Its not about XGBoost, its more about feature engineering, can try few filters and engineer good features. In my earlier project, I developed for every hour odds of rare occurrences, which worked very well for the client data. Added my two cents, hope you achieve best forcests. Happy forecasting!

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u/Capable-Package6835 1h ago

XGBoost is a go-to model for many applications. Easy to train and typically yield decent accuracy. If you didn't get a good result, I recommend to tinker with your features and preprocessing before jumping to another model.