Quiz and summary
Contents
6.3. Quiz and summary¶
6.3.1. Quiz 6¶
Complete Quiz 6 to check your understanding of this topic. You are advised to score at least 50% to proceed to the next topic.
6.3.2. Summary¶
In traditional machine learning, feature selection is a core part of the process to improve accuracy and prevent overfitting. In fact, feature selection can help improve the transparency of a machine learning model since it tells us what the model finds important. In some cases, the selected features be cross-checked with domain experts, such as in clinical settings. Furthermore, we also learned about how regularisation can help prevent overfitting and improve your models.
In this topic, you learnt:
Methods of feature selection.
How to regularise linear models.
6.3.3. References and further reading¶
This material is based on the following resources:
The Textbook: James G, Witten D, Hastie T, Tibshirani R., An Introduction to Statistical Learning, Second Edition, Springer, 2021. PDF [James et al., 2021]