Which data encoding scheme maps text to a random yet deterministic value?

The correct choice is indeed hash encoding because this method transforms textual data into a fixed-size string of characters, which is typically a hexadecimal string. The hallmark of hash encoding is that it maps input data to a random yet deterministic value, meaning that the same input will consistently yield the same output. This is particularly useful in applications such as data integrity validation, where you want to ensure that the data has not been altered.

Hash encoding uses hash functions that take an input and produce a unique, fixed-length output. The randomness helps to evenly distribute inputs across the output range, while the deterministic aspect assures that identical inputs will generate identical hashes, aiding in quicker data retrieval and comparison without needing to store the original text.

The other choices serve different purposes. Frequency-based encoding relies on the frequency of a term within the dataset, which does not yield a random mapping. One-hot encoding represents categorical variables as binary vectors and does not involve randomness. Target mean encoding uses statistical measures based on the target variable, again lacking the characteristics of a hashing scheme.