Building Algorithm Flow in a Workbook Canvas
The workbook canvas is your experimental area.
You can create, run, and train your algorithm flow in workbook canvas using a simple drag-and-drop method, to add datasets and algorithms.
The table given below provides major differences between the workbook and workflow.
Workbook Canvas | Workflow Canvas |
---|
It is an experimental area where you train your datasets and algorithms. | It is the production area where trained datasets are used to publish your algorithms as models. |
It also contains classification and regression algorithms, along with other algorithms. | It contains all algorithms present in the workbook, except classification and regression algorithms. |
You cannot schedule algorithms to run later. | You can schedule your final algorithms to run automatically at specific time intervals. |
To use canvas, follow the steps given below.

Notes: | - It is recommended to save your Workbook after every step. This ensures all the changes are saved.
- To save the workbook, click the Save icon (
).
|
- Open the Workspace where you want to create your workbook. Refer to Changing Workspace.
- Create a Workbook. Refer to Creating a Workbook.
Use the drag-and-drop method to insert readers and algorithms from the Task Pane into the canvas.
Note:
| You can also double-click on the reader or algorithm to add it to the canvas. |

Click the reader/algorithm and click the Node Connector, and then click the other reader/algorithm that you want to join with it.
Similarly, join the other elements.
Note:
| You can also join a single element to multiple elements if required. |

- Click the reader/algorithm and select the Properties displayed on the right-hand side.
Here we have selected Data Fields (columns in your dataset) for the selected reader.
Click the reader/algorithm and click the vertical ellipsis (
). The functions available for the elements are as follows.

Note:
| Publish as a model is available only for Machine Learning, Regression, and Classification algorithms. |
The table given below describes the functions present on the reader or algorithm.
Icon | Icon Name | Description |
| Run | It runs the selected node of the algorithm. Note: The predecessor node is expected to be successfully executed. |
| Run from Node | It runs all the nodes below, from the selected node. Note: All nodes before this node are expected to be successfully executed. |
| Run till Node | It runs all the nodes from the top node, until the selected node. |
| Explore | It lets you explore the result of the selected node. Note: You can explore only after the algorithm is successfully executed. |
| Publish as a Model | It publishes the algorithm flow as a model. Note: You can publish models only in Data integrator for Machine Learning algorithms. |
| Delete | It deletes the node. |
- Click the Save icon (
) on the function pane, to save the algorithm flow.
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