Dimensionality Reduction
The process of reducing the number of random variables under consideration in a dataset.
Description
Dimensionality reduction is the process of reducing the number of features in a dataset while retaining as much information as possible. It's used to simplify datasets, reduce computational complexity, and mitigate the curse of dimensionality.
Examples
- ๐งฎ Principal Component Analysis (PCA)
- ๐บ๏ธ t-SNE
- ๐ง Autoencoders
Applications
Related Terms
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