Feature Selection

Feature selection is the process of choosing a subset of the most relevant features from your original dataset. The goal is to reduce the dimensionality of the data by removing irrelevant, redundant, or noisy features. This can lead to simpler models, improved model performance (e.g., accuracy, speed), and better understanding of the underlying data.

Visit the following resources to learn more:

• @article@What is Feature Selection? | IBM