About this document
3.20 - Feature Selection. Introduction by Mikhael Felipe is a document available to read on EtoBox.
The document discusses feature selection techniques in data-driven science, particularly in the context of chemical data analysis. It covers methods such as SIMCA, wavelets, and genetic algorithms, emphasizing the importance of reducing dimensionality and eliminating irrelevant features to improve classification accuracy. The document highlights that effective feature selection is crucial for managing underdetermined data sets where the number of measurements exceeds the number of samples.
- Author
- Mikhael Felipe
- Language
- EN