December 2018
Beginner to intermediate
684 pages
21h 9m
English
Content preview from Hands-On Machine Learning for Algorithmic Trading
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Perplexity
Perplexity, when applied to LDA, measures how well the topic-word probability distribution recovered by the model predicts a sample, for example, unseen text documents. It is based on the entropy H(p) of this distribution p and computed with respect to the set of tokens w:
Measures closer to zero imply the distribution is better at predicting the sample.