What is heterogeneous feature representation in ensembles?

Heterogeneous feature representation uses different feature transformations across ensemble models.

In advanced ensembles, each base model may use a different feature representation such as raw features, PCA-transformed features, polynomial features, or embeddings. This increases diversity beyond model type differences. It allows each model to learn different views of the same data, improving ensemble robustness in complex feature spaces.