So perplexity represents the number of sides of a fair die that when rolled, produces a sequence with the same entropy as your given probability distribution. Number of States OK, so now that we have an intuitive definition of perplexity, let's take a quick look at how it is affected by the number of states in a model.

In the Coursera NLP course , Dan Jurafsky calculates the following perplexity: Operator(1 in 4) Sales(1 in 4) Technical Support(1 in 4) 30,000 names(1 in 120,000 each) He says the Perplexity is 53...

Nov 28, 2018 · The perplexity can be interpreted as a smooth measure of the effective number of neighbors. The performance of SNE is fairly robust to changes in the perplexity, and typical values are between 5 and 50. What this effective number of neighbors would mean? Should I understand perplexity value as expected number of nearest neighbors to the point ...

Jan 12, 2018 · Having negative perplexity apparently is due to infinitesimal probabilities being converted to the log scale automatically by Gensim, but even though a lower perplexity is desired, the lower bound value denotes deterioration (according to this), so the lower bound value of perplexity is deteriorating with a larger number of topics in my figures ...

Would comparing perplexities be invalidated by the different data set sizes? No. I copy below some text on perplexity I wrote with some students for a natural language processing course (assume log log is base 2): In order to assess the quality of a language model, one needs to define evaluation metrics. One evaluation metric is the log-likelihood of a text, which is …

The perplexity, used by convention in language modeling, is monotonically decreasing in the likelihood of the test data, and is algebraicly equivalent to the inverse of the geometric mean per-word likelihood. A lower perplexity score indicates better generalization performance. I.e, a lower perplexity indicates that the data are more likely.

If I understand it correctly, this means that I could calculate the perplexity of a single sentence. What does it mean if I'm asked to calculate the perplexity on a whole corpus?

I'm confused about how to calculate the perplexity of a holdout sample when doing Latent Dirichlet Allocation (LDA). The papers on the topic breeze over it, making me think I'm missing something ob...

Mar 8, 2018 · I played around with the t-SNE implementation in scikit-learn and found that increasing perplexity seemed to always result in a torus/circle. I couldn't find any mentions about this in literature.

Nov 12, 2020 · I am trying to find a way to calculate perplexity of a language model of multiple 3-word examples from my test set, or perplexity of the corpus of the test set.