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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
Comparing Perplexities With Different Data Set Sizes 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 computed as follows
Finding the perplexity of multiple examples - Cross Validated 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
clustering - Why does larger perplexity tend to produce clearer . . . Why does larger perplexity tend to produce clearer clusters in t-SNE? By reading the original paper, I learned that the perplexity in t-SNE is 2 2 to the power of Shannon entropy of the conditional distribution induced by a data point
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