The Model Builder interface
Introduction to the Decision Optimization for Data Science Experience interface.
When you add a new model to a project, you can choose between creating a Machine Learning model or a Decision Optimization model.
The Decision Optimization model builder allows you to create prescriptive models. Optimization models allow you to focus on a specific business problem that you want to solve.
With the Decision Optimization model builder, you can create several scenarios, using different data sets and optimization models. This allows you to create and compare different scenarios and see how big an impact changes can have on a given problem.
Select Data view
When you create a new Decision Optimization model in your project, the Select Data view opens. In this view you can choose the data that you want to add to
your model. Click add data set to browse
and select your files and click open. Note that only
csv files can be
imported in Decision Optimization for Data Science Experience. If you repeat this
selection of data at any time and choose a file with the same name as one already loaded, you will
replace the current version of this file with the latest version you have added.
When you have added your data files, they appear listed in the Select Data view. You can preview a table by clicking on it. This opens the table in a window, click either the Close or Select this data set buttons underneath the table (resize your window if necessary) to close this window. Select the files you want to import to a scenario and click Import. If you repeat the import of a file at any time you will end up with a second version of the file. This can be useful if you want to use different versions of the same data table.
Prepare Input Data view
- Rename or delete a table.
- Edit the data directly in a table (in full or expanded table mode).
Create a new empty Python optimization model in your project. Use this option to generate a Python model from your current scenario.
Use the Modeling Assistant. Use this option to develop a model with the Modeling Assistant. This option is currently only available for scheduling problems.
Import a Python optimization model from an existing Notebook or from an external file. Use this option to import a Notebook from your local machine or to use a Notebook you have already imported into Decision Optimization for Data Science Experience.
Once you have created a model, the Reinitialize option appears in the upper-left of the window. If you click Reinitialize, you return to the Model wizard. Note that if you create a new model, the previous one is deleted.
When your run completes successfully, the solution is displayed in one or several tables. The result tables are automatically displayed in alphabetic order. Note that the result tables are not editable.
In the Solution view, you can also find information about the run status (processed, stopped, or failed) and download run logs.
When you create a new Decision Optimization model, a scenario is automatically created along with the model. A scenario contains data sets, a model, and a solution.
- Make sure a specific model works with a variety of data
- See how different data sets impact the solution to a given problem
- See how a model formulation impacts the solution to a given problem
The Scenario panel allows you to easily manage scenarios in a Decision Optimization model.
To open the Scenario panel, click the Scenario button .
- Create new scenarios (duplicate your current scenario or create a new scenario from scratch).
- Select the scenario you want to work in.
- See existing scenarios and their details (input data, model, solution).
- Manage existing scenarios (duplicate, rename, delete).
The Dashboard allows you to configure the graphical representation of input data and solutions for one or several scenarios. The Dashboard is common to all scenarios in a Decision Optimization model.
The Dashboard helps you compare the different scenarios you have created in order to validate models and business decisions.
The following widgets are available:
Add simple text notes to the Dashboard.
Present input data and solution in tables, with a search and filtering feature.
Present input data and solution in charts.
Display the solution to a scheduling problem in a Gantt chart.
This widget is only suitable for scheduling problems modeled with the Modeling Assistant. Apart from its title, this widget is not currently editable.
You can edit the widgets in the Dashboard Editor by clicking the Configure Widget (pencil) icon in a widget. You can then customize it either in the Editor or by editing the JSON code. The Editor allows you to easily change the name of your widget and select the source of the data you want to display in your dashboard. The JSON editor gives you more advanced editing possibilities. As you make changes to a widget in the Dashboard Editor, a preview is also displayed showing you your changes. You can then choose to save your changes by clicking OK which will close the Dashboard Editor. Or you can select Cancel to abandon your changes.
For more information about the JSON widget syntax, refer to the following section: Dashboard widgets syntax.
The JSON editor uses the Vega-Lite syntax, for more information see Vega-Lite - A High-Level Visualization Grammar.
You can download your dashboard as a JSON file, containing the dashboard definition and the data, making it easier for you to share your findings with your collaborators.
You can create different dashboard pages for different scenarios or combine scenarios on the same page.
You can add pages to your dashboard by double-clicking the plus sign. You can then customize what is displayed on each page. To edit a page, click the Edit Dashboard (pencil) icon in the upper-right of the dashboard. In the Dashboard Editor you can edit the page name, reorder and add pages. Clicking OK in the Dashboard Editor saves your updates and closes the editor. Or you can select Cancel to abandon your changes. To delete a page, click the page tab and a delete button appears in the tab.