Use the Latent Dirichlet Allocation (LDA) topic model to analyze text data.
Create a function which cleans and preprocesses text data for analysis.
Train a simple text classifier on word frequency counts using a bag-of-words model.
Decide on a suitable number of topics for a latent Dirichlet allocation (LDA) model.
Compare latent Dirichlet allocation (LDA) solvers by comparing the goodness of fit and the time taken to fit the model.
Extract the text data from text, HTML, Microsoft® Word, PDF, CSV, and Microsoft Excel® files and import it into MATLAB® for analysis.
Parse HTML code and extract the text content from particular elements.