Incremental Learning

Incremental Learning

Incremental Learning is located under Textual Analysis (  ) in Clustering, in the left task pane. Use the drag-and-drop method to use the algorithm in the canvas. Click the algorithm to view and select different properties for analysis.



Properties of Incremental Learning

The available properties of Incremental Learning are as shown in the figure given below.


The table given below describes the different fields present on the properties of Incremental Learning.

Field

Description

Remark

RunIt allows you to run the node.-
ExploreIt allows you to explore the successfully executed node.-
Vertical Ellipses

The available options are

  • Run till node
  • Run from node
  • Publish as a model
  • Publish code
-

Task Name

It is the name of the task selected on the workbook canvas.

You can click the text field to edit or modify the name of the task as required.

Text

It allows you to select Independent variables.

  • You can select more than one variable.
  • You can select any type of variable.

Number of Clusters

It allows you to enter the number of clusters you want to create.

The default value is 3.

Advanced

Threshold


The default value is 0.5.

Branching Factor

It allows you to enter the number of child nodes that can be created at each node.

The default value is 50.

Example of Incremental Learning

Consider a dataset of Musical Instruments review. A snippet of input data is shown in the figure given below.


After using the Incremental Learning, the following results are displayed.


As seen in the above figure, the data is divided into three clusters. A pie chart of the clusters, each cluster's size, and the Silhouette Score are displayed.


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