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text analytics toolbox documentation -凯发k8网页登录

analyze and model text data

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.

using machine learning techniques such as lsa, lda, and word embeddings, you can find clusters and create features from high-dimensional text datasets. features created with text analytics toolbox can be combined with features from other data sources to build machine learning models that take advantage of textual, numeric, and other types of data.

get started

learn the basics of text analytics toolbox

text data preparation

import text data into matlab® and preprocess it for analysis

modeling and prediction

develop predictive models using topic models and word embeddings

display and presentation

visualize text data and models using word clouds and text scatter plots

language support

information on language support in text analytics toolbox

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