Creating an Experiment
Creating an Experiment is a two-step process that involves configuration and selection of the algorithm type as steps.
Last updated
Creating an Experiment is a two-step process that involves configuration and selection of the algorithm type as steps.
Last updated
A user can create a supervised learning (data science) experiment by choosing the Create Experiment option.
Please Note: The Create Experiment icon is provided on the Dataset List page under the Dataset tab of a Repo Sync Data Science Project.
Navigate to the Dataset List page.
Select a Dataset from the list.
Click the Create Experiment icon.
The Configure tab opens (by default) while selecting the Create Experiment option.
Provide the following information:
Provide a name for the experiment.
Provide Description (optional).
Select a Target Column.
Select a Data Preparation from the drop-down menu.
Use check-box to select a Data Preparation from the displayed drop-down.
Select columns that need to be excluded from the experiment.
Use check-box to select a field to be excluded from the experiment.
Please Note: The selected fields will not be considered while training the Auto ML model experiment.
Click the Next option.
The user gets redirected to the Select Experiment Type tab.
Select a prediction model using the checkbox.
Based on the selected experiment type a validation notification message appears.
Click the Done option.
A notification message appears.
Navigate to the AutoML list page.
The newly created experiment gets added to the list.
Another notification message appears to inform the user that the model training has started. The same is indicated through the Status column of the model. The Status for such models will be Running.
After the experiment is completed, a notification message appears stating that the model is trained. The Status for a trained model will be indicated as Completed.
Please Note:
The unsuccessful experiments are indicated as Failed under the status. The View Report is mentioned in red color for the Failed experiments.
Refer to the Data Science Lab Quick Start Flow page to get an overview of the Data Science Lab module in a nutshell.
