Topic Model । Latent Dirichlet Allocation । Collapsed Gibbs Sampling । BBC news dataset । python
Topic Model | Latent Dirichlet Allocation | Collapsed Gibbs Sampling | python implementation | Bayesian
Topics found using python implementation for collapsed-Gibbs-sampling-based LDA from BBC news classification dataset (obtained after running MCMC for a burn-in period):
Topic 1 - business (defined by the words: dollar, growth, economy, market, company)
Topic 2 - entertainment (defined by the words: film, music, awards)
Topic 3 - sport (defined by the words: game, play, win, players)
Topic 4 - tech (defined by the words: mobile, technology, phone, software,, computer)
Topic 5 - politics (defined by the words: labour, government, election. party, minister)
The topics change over iterations (as can be seen from the top-10 word count histograms for the topics)
The heatmaps show how the word-topic (5 topic clusters are created with a few non-overlapping set of words in the end) and topic-document distributions change over iterations
#topicmodel #lda #python #unsupervised #unsupervisedlearning #nlp #machinelearning #mcmc #gibbs #bayesian
Смотрите видео Topic Model । Latent Dirichlet Allocation । Collapsed Gibbs Sampling । BBC news dataset । python онлайн без регистрации, длительностью часов минут секунд в хорошем качестве. Это видео добавил пользователь Image Processing, CV, ML, DL & AI Projects 16 Октябрь 2023, не забудьте поделиться им ссылкой с друзьями и знакомыми, на нашем сайте его посмотрели 14 раз и оно понравилось людям.