What Hashing Trick Meaning, Applications & Example
Technique for reducing dimensionality of categorical variables.
What is Hashing Trick?
The Hashing Trick is a technique used to convert categorical data or high-dimensional features into fixed-length vectors. By applying a hash function, the technique maps data into a smaller vector space, reducing memory usage and computational complexity while maintaining most of the original information.
Types of Hashing Trick
- Feature Hashing: Hashes input features into a fixed-size vector, often used in natural language processing tasks to handle large vocabularies.
- Hashing Vectorization: Converts high-dimensional text or categorical data into a lower-dimensional vector representation.
Applications of Hashing Trick
- Text Classification: Reduces the dimensionality of text data for efficient processing while preserving key information.
- Recommendation Systems: Helps in encoding user preferences and item characteristics in a compact form for fast lookups.
- Search Engines: Reduces the space needed for indexing large datasets, improving search speed.
Example of Hashing Trick
In a text classification task, a model might use the Hashing Trick to convert a large vocabulary into a fixed-length vector of size 10,000. Instead of using a one-hot encoding for each word, which would require a huge amount of memory, the Hashing Trick reduces the dimensionality while still capturing the essential features of the words.