intuition - What is perplexity? - Cross Validated
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.
information theory - Calculating Perplexity - Cross Validated
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...
Intuition behind perplexity parameter in t-SNE
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 ...
How to find the perplexity of a corpus - Cross Validated
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text mining - How to calculate perplexity of a holdout with Latent ...
Perplexity is seen as a good measure of performance for LDA. The idea is that you keep a holdout sample, train your LDA on the rest of the data, then calculate the perplexity of the holdout. The perplexity could be given by the formula:
machine learning - Why does lower perplexity indicate better ...
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.
Comparing Perplexities With Different Data Set Sizes
Under this uniform language model, the perplexity is equal to the size of the vocabulary. Generally, perplexity captures the effective vocabulary size under the model. For instance, a trigram model described above has a factual branching factor of 109, even though it operates over the vocabulary of 19,979.
Inferring the number of topics for gensim's LDA - perplexity, CM, …
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 ...
clustering - Why does larger perplexity tend to produce clearer ...
Mar 28, 2019 · The larger the perplexity, the more non-local information will be retained in the dimensionality reduction result. Yes, I believe that this is a correct intuition. The way I think about perplexity parameter in t-SNE is that it sets the effective number …
Finding the perplexity of multiple examples - Cross Validated
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. As the test set, I have a paragraph which I've split into 3-word examples like this: if the corpus is "Hello my name is Jack.", my 3-word examples would be "Hello my name", "my name is ...