> For the complete documentation index, see [llms.txt](https://docs.sov.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sov.ai/feature-processing.md).

# Feature Processing

- [Extract Features](https://docs.sov.ai/feature-processing/extract-features.md): The feature extractor module generates features that can be categorized into several types based on the nature of the calculations.
- [Neutralize Features](https://docs.sov.ai/feature-processing/neutralize-features.md): The feature extractor module generates features that can be categorized into several types based on the nature of the calculations.
- [Select Features](https://docs.sov.ai/feature-processing/select-features.md): The feature selection module in the sovai library provides various methods to identify and select the most important features from financial datasets.
- [Dimensionality Reduction](https://docs.sov.ai/feature-processing/dimensionality-reduction.md): Implements multiple reduction techniques including PCA, SVD, Factor Analysis, Gaussian Random Projection, and UMAP.
- [Feature Importance](https://docs.sov.ai/feature-processing/feature-importance.md): The feature importance module in the sovai library offers multiple unsupervised algorithms to quantify the significance of each feature in financial datasets.