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...
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 …
autoencoders - Codebook Perplexity in VQ-VAE - Cross Validated
Jan 5, 2023 · When calculating perplexity, we are effectively calculating the codebook utilization. In the example above, if you change the low and high to a narrow range, then out of the 1024 codebook entries that we could have picked/predicted …
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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Perplexity calculation in variational neural topic models
Since $\log p(X)$ is intractable in the NVDM, we use the variational lower bound (which is an upper bound on perplexity) to compute the perplexity following Mnih & Gregor (2014).
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.
entropy - Perplexity of the following example - Cross Validated
Perplexity formula in the t-SNE paper vs. in the implementation Hot Network Questions I2C address conflict workaround through delayed signal propagation or delayed powerup
Perplexity and cross-entropy for n-gram models
Jun 16, 2017 · One is that, because of the exponent, improvements in perplexity "feel" like they are more substantial than the equivalent improvement in entropy. Another is that before they started using perplexity, the complexity of a language model was reported using a simplistic branching factor measurement that is more similar to perplexity than it is to ...