make_sampling_table
Generates a word rank-based probabilistic sampling table.
Description
Generates a word rank-based probabilistic sampling table.
Usage
make_sampling_table(size, sampling_factor = 1e-05) Arguments
| Arguments | Description |
|---|---|
| size | Int, number of possible words to sample. |
| sampling_factor | The sampling factor in the word2vec formula. |
Details
Used for generating the sampling_table argument for skipgrams(). sampling_table[[i]] is the probability of sampling the word i-th most common word in a dataset (more common words should be sampled less frequently, for balance). The sampling probabilities are generated according to the sampling distribution used in word2vec: p(word) = min(1, sqrt(word_frequency / sampling_factor) / (word_frequency / sampling_factor)) We assume that the word frequencies follow Zipf’s law (s=1) to derive a numerical approximation of frequency(rank): frequency(rank) ~ 1/(rank * (log(rank) + gamma) + 1/2 - 1/(12*rank)) where gamma is the Euler-Mascheroni constant.
Value
An array of length size where the ith entry is the probability that a word of rank i should be sampled.
Note
The word2vec formula is: p(word) = min(1, sqrt(word.frequency/sampling_factor) / (word.frequency/sampling_factor))
See Also
Other text preprocessing: pad_sequences(), skipgrams(), text_hashing_trick(), text_one_hot(), text_to_word_sequence()