Topic Modeling, Topic Noise Modeling, Unsupervised Learning, Twitter Data, Text Data.
d, assign w to zᵢ or the noise distribution H, based on the probabilities of w in zᵢ and H (Figure 5). 3. Re-approximate the topic distribution of d given the new topic-word assignments Repeat the above for X iterations (usually 500 or 1,000 in practice) The hyperparameter k defines the number of