This article outlines the different available insights in the Engine in order to successfully evaluate trained supervised machine learning models.
Step 1 - Go to a model page
From the model leaderboard or the model list, select a successfully trained model
From model leaderboard
From model list
Step 2 - View all the available insight tools from the model summary tab
All the available tools to examine a model are listed under the “Insight” section of the model summary tab. Currently, the available tools are:
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Performance - metrics to evaluate prediction quality
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Feature importance - impact score of different features on a model prediction
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Prediction explanation - prediction explanation examples taken from the training data
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What-if analysis tool - individual predictions to explore different input value scenarios
The insight section under model summary tab
Step 3 - Navigate to the insights tab and explore different tools
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From the model summary tab, click the tab “Insights”
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Select the tool of interest and view the details
To quickly go to specific tools from the model summary tab, click on the link in a particular tool card. For example, this is how you can quickly access the different insights and the batch prediction tool:
