Feature Vector Hashing Task

A Feature Vector Hashing Task is a featurization task that can produce hashed feature (attributes are mapped via a hash).

• • …
• Counter-Example(s):
  • One-Hot Feature Tuple.
• See: Hashing, Predictor Feature, Dimensionality Reduction, Bloom Filter, Learning with Counts, Count-Min Sketches.

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References

2013

• http://en.wikipedia.org/wiki/Feature_hashing
  • In machine learning, feature hashing, also known as the hashing trick, is a fast and space-efficient way of vectorizing features, i.e. turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values as indices directly, rather than looking the indices up in an associative array.

2009

• (Weinberger et al., 2009) ⇒ Kilian Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, and Josh Attenberg. (2009). “Feature Hashing for Large Scale Multitask Learning.” In: Proceedings of the 26th Annual International Conference on Machine Learning. doi:10.1145/1553374.1553516

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