Display and Presentation
Visualize text data and models using word clouds and text scatter plots
Text Analytics Toolbox™ provides algorithms and visualizations for preprocessing, analyzing, and modeling text data. Visualize large collections of text data using word frequency counts and LDA models using word clouds. Explore word embeddings using text scatter plots.
Functions
wordcloud |
Create word cloud chart from text, bag-of-words model, bag-of-n-grams model, or LDA model |
textscatter |
2-D scatter plot of text |
textscatter3 |
3-D scatter plot of text |
wordCloudCounts |
Count words for word cloud creation |
Properties
TextScatter Properties | Control text scatter chart appearance and behavior |
Topics
Text Visualization
- Visualize Text Data Using Word Clouds
This example shows how to visualize text data using word clouds. - Visualize Word Embeddings Using Text Scatter Plots
This example shows how to visualize word embeddings using 2-D and 3-D t-SNE and text scatter plots.
Topic Modeling Visualization
- Visualize LDA Topics Using Word Clouds
This example shows how to visualize the words in Latent Dirichlet Allocation (LDA) model topics. - Visualize LDA Topic Probabilities of Documents
This example shows how to visualize the topic probabilities of documents using a latent Dirichlet allocation (LDA) topic model. - Visualize Document Clusters Using LDA Model
This example shows how to visualize the clustering of documents using a Latent Dirichlet Allocation (LDA) topic model and a t-SNE plot. - Visualize LDA Topic Correlations
这个例子展示了如何分析相关性的赌注ween topics in a Latent Dirichlet Allocation (LDA) topic model. - Visualize Correlations Between LDA Topics and Document Labels
This example shows how to fit a Latent Dirichlet Allocation (LDA) topic model and visualize correlations between the LDA topics and document labels.