|  | Element | Description |
|---|---|---|
| ![](images/icon-1.png) | Selected word | Displays details about the selected word. (The term *word* here equates to an [*n-gram*](glossary/index#ngram), which can be a sequence of words.) <br><br>Mouse over a word to select it. Words that appear more frequently display in a larger font size in the **Word Cloud**, and those that appear less frequently display in smaller font sizes.|
| ![](images/icon-2.png) | Coefficient | Displays the [coefficient](coefficients#coefficientpreprocessing-information-with-text-variables) value specific to the word.|
| ![](images/icon-3.png) | Color spectrum | Displays a legend for the color spectrum and values for words, from blue to red, with blue indicating a negative effect and red indicating a positive effect. |
| ![](images/icon-4.png) | Appears in # rows| Specifies the number of rows the word appears in. |
| ![](images/icon-5.png) | Filter stop words | Removes stop words (commonly used terms that can be excluded from searches) from the display. |
| ![](images/icon-6.png) | Export | Allows you to [export](export-results) the **Word Cloud**. |
| ![](images/icon-7.png) | Zoom controls | Enlarges or reduces the image displayed on the canvas. Alternatively, double-click on the image. To move areas of the display into focus, click and drag. |
| ![](images/icon-8.png) | Select class | For multiclass projects, selects the class to investigate using the **Word Cloud**. |

??? info "Word Cloud availability"
    You can access **Word Cloud** from either the **Insights** page or the Leaderboard. Operationally, each version of the model behaves the same&mdash;use the Leaderboard tab to view a **Word Cloud** while investigating an individual model and the **Insights** page to access, and compare, each **Word Cloud** for a project. Additionally, they are available for multimodal datasets (i.e., datasets that mix images, text, categorical, etc.)&mdash;a **Word Cloud** is displayed for all text from the data.

The **Word Cloud** visualization is supported in the following model types and blueprints:

* Binary classification:
    * All variants of ElasticNet Classifier (linear family models) with the exception of TinyBERT ElasticNet classifier and FastText ElasticNet classifier
    * LightGBM on ElasticNet Predictions
    * Text fit on Residuals
    * Extended support for multimodal datasets (with single Auto-Tuned N-gram)

* Multiclass:
    * Stochastic Gradient Descent with at least 1 text column with the exception of TinyBERT SGD classifier and FastText SGD classifier

* Regression:
    * Ridge Regressor
    * ElasticNet Regressor
    * Lasso Regressor
    * Single Auto-Tuned Multi-Modal
    * LightGBM on ElasticNet Predictions
    * Text fit on Residuals

* Keras

!!! note
    The **Word Cloud** for a model is based on the data used to train that model, not on the entire dataset. For example, a model trained on a 32% sample size will result in a **Word Cloud** that reflects those same 32% of rows.

See [Text-based insights](analyze-insights#text-based-insights) for a description of how DataRobot handles single-character words.
