intuition - What is perplexity? - Cross Validated
I came across term perplexity which refers to the log-averaged inverse probability on unseen data. Wikipedia article on perplexity does not give an intuitive meaning for the same. This perplexity
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 ...
clustering - Why does larger perplexity tend to produce clearer ...
Mar 28, 2019 · 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.
text mining - How to calculate perplexity of a holdout with Latent ...
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...
How to find the perplexity of a corpus - Cross Validated
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?
autoencoders - Codebook Perplexity in VQ-VAE - Cross Validated
Jan 5, 2023 · For example, lower perplexity indicates a better language model in general cases. The questions are (1) What exactly are we measuring when we calculate the codebook perplexity in VQ models? (2) Why would we want to have large codebook perplexity? What is the ideal perplexity for VQ models? Sorry if my questions are unclear.
Perplexity formula in the t-SNE paper vs. in the implementation
Mar 11, 2019 · The perplexity formula in the official paper of t-SNE IS NOT the same as in its implementation. In the implementation (MATLAB): % Function that computes the Gaussian kernel values given a vector of % squared Euclidean distances, and the precision of the Gaussian kernel. % The function also computes the perplexity of the distribution.
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.
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 ...