Dimension reduction is the process of decreasing the number of dimensions used to represent data or a feature vector. It often converts high-dimensional representations into lower-dimensional embeddings to improve efficiency, visualization, or generalization.
Decreasing the number of dimensions used to represent a particular feature in a feature vector, typically by converting to an embedding vector.