Feature Hashing

Feature hashing is used to control representation cost in very high-dimensional or open-ended categorical spaces. Each category or token is mapped into a fixed-dimensional vector space using a hash function. This is especially efficient in text data, advertising systems, and large-scale logistics datasets. Its drawback is that different inputs can collide into the same hashed location. Even so, it remains a widely used engineering solution in high-scale systems.