Text Modeling Visualizers¶
Yellowbrick provides the
yellowbrick.text module for text-specific visualizers. The
TextVisualizer class specifically deals with datasets that are corpora and not simple numeric arrays or DataFrames, providing utilities for analyzing word dispersion and distribution, showing document similarity, or simply wrapping some of the other standard visualizers with text-specific display properties.
We currently have four text-specific visualizations implemented:
- Token Frequency Distribution: plot the frequency of tokens in a corpus
- t-SNE Corpus Visualization: plot similar documents closer together to discover clusters
- UMAP Corpus Visualization: plot similar documents closer together to discover clusters
- Dispersion Plot: plot the dispersion of target words throughout a corpus
- PosTag Visualization: plot the counts of different parts-of-speech throughout a tagged corpus
Note that the examples in this section require a corpus of text data, see loading a text corpus for more information.
from yellowbrick.text import FreqDistVisualizer from yellowbrick.text import TSNEVisualizer from yellowbrick.text import UMAPVisualizer from yellowbrick.text import DispersionPlot from yellowbrick.text import PosTagVisualizer from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.feature_extraction.text import CountVectorizer