intuition - What is perplexity? - Cross Validated
网页First of all, perplexity has nothing to do with characterizing how often you guess something right. It has more to do with characterizing the complexity of a stochastic sequence. We're looking at a quantity, 2−∑x p(x)log2 p(x) 2 − ∑ x p (x) log 2 p (x) Let's first cancel out the log and the exponentiation.
clustering - Why does larger perplexity tend to produce clearer ...
网页2019年3月28日 — The larger the perplexity, the more non-local information will be retained in the dimensionality reduction result. When I use t-SNE on two of mine test datasets for dimensionality reduction, I observe that the clusters found by t-SNE will become consistently more well-defined with the increase of perplexity.
information theory - Calculating Perplexity - Cross Validated
网页1. Yes, but the equation used by Jurafsky is P (w1, w2, ..., wN)^- (1/N) – Anonymous. Jun 11, 2014 at 18:26. so if all things are equal in likelihood then the probability of any outcome is the frequency of that outcome divided by the frequency of all possible outcomes. 4*4*30k = 480k alternatives. The likelihood of any one outcome is one in 480k.
autoencoders - Codebook Perplexity in VQ-VAE - Cross Validated
网页2023年1月5日 — 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 by our model, we only ended up picking a small range.
machine learning - Why does lower perplexity indicate better ...
网页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.
How to find the perplexity of a corpus - Cross Validated
网页Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
text mining - How to calculate perplexity of a holdout with Latent ...
网页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:
Intuition behind perplexity parameter in t-SNE
网页2018年11月28日 — 7. While reading Laurens van der Maaten's paper about t-SNE we can encounter the following statement about perplexity: 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.
Perplexity calculation in variational neural topic models
网页To evaluate the effectiveness of their model, they use perplexity, defined as exp(− 1 NΣNn 1 Lnlog p(Xn)) e x p (− 1 N Σ n N 1 L n log p (X n)). Where N N is number of documents, Ln L n is number of words in document n n, and p(Xn) p (X n) is the probability of observing document Xn X n (calculated by taking the product of the per-word ...
Inferring the number of topics for gensim's LDA - perplexity, CM, …
网页2018年1月12日 — Metadata were removed as per sklearn recommendation, and the data were split to test and train using sklearn also (subset parameter). I trained 35 LDA models with different values for k, the number of topics, ranging from 1 to 100, using the train subset of the data. Afterwards, I estimated the per-word perplexity of the models using gensim's ...