Exercise 3 — Error analysis and the final test

Guided practice6 min
Time
30-40 min
You need
the kit, the venv active, python data/make_dataset.py done, Exercise 2 finished
Deliverable
week06/results.md

The lab kit of the course: https://github.com/hrhouma2/aiopsatlas-ml-data-diagnostics-labs-en

Goal

NorthPeak wants one page with the numbers. You will train the tuned forest of Exercise 2 and the logistic regression of Week 5 on January to September. Then you open October to December, once. You compute the AUC, a confusion matrix, the feature importance, and the errors by machine type and by month. You write everything to week06/results.md. After that, the test set is closed.

Preview — the rest of the lesson is for enrolled readers.

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This lesson is part of the “Week 6 — Model selection and validation” module

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