Название: MATLAB Text Analytics Toolbox User's Guide (R2023a)
Автор: The MathWorks
Издательство: The MathWorks, Inc
Год: March 2023
Страниц: 336
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Text Analytics Toolbox provides algorithms and visualizations for preprocessing, analyzing, and modeling text data. Models created with the toolbox can be used in applications such as sentiment analysis, predictive maintenance, and topic modeling. Text Analytics Toolbox includes tools for processing raw text from sources such as equipment logs, news feeds, surveys, operator reports, and social media. You can extract text from popular file formats, preprocess raw text, extract individual words, convert text into numerical representations, and build statistical models.

Classify Documents Using Document Embeddings: This example shows how to train a document classifier by converting documents to feature vectors using word embeddings. Most Machine Learning techniques require feature vectors as input to train a classifier. A word embedding maps individual words to vectors. You can use a word embedding to map a document to a single vector by combining the word vectors, for example, by calculating the mean vector to create a document vector. Given a data set of labeled document vectors, you can then train a Machine Learning model to classify these documents.