Insights
Unleashing the power of feature importance analysis with Insights
What are "Insights"?
Insights represent an advanced feature importance calculator designed to comprehensively understand your model's performance on a training set. This will enable you to separate genuine from high-risk customers. With this cutting-edge functionality, you can now unravel the importance of each signal, gaining full explainability and valuable insights into the factors that drive your model's predictions.
By collecting a wide range of data the feature will allow you to easily identify trustworthy customers. At the same time, you can use Insights to red-flag suspicious activity, thus isolating potential fraudsters.
How does it work?
โInsightsโ employs sophisticated algorithms to calculate scores for each input feature based on their impact on the model's predictions. A higher score represents a greater influence within the model, helping you understand, prioritize, and optimize your rule sets for enhanced model performance.
![](https://files.readme.io/be2f9c8-Feature-Insights_Upload.gif)
Begin by selecting the "Insights" tab on the Trustull dashboard. Upload your training set effortlessly, defining "OK" and "KO" users with a simple click, and, watch as the platform calculates feature importance scores without any coding. Explore the results instantly, gaining valuable insights to optimize, debug, and enhance decision-making for your risk modeling projects.
![](https://files.readme.io/6448dc5-Feature-Insights_Analysis.gif)
It's a hassle-free process, putting the power of model interpretation at your fingertips!
Key Benefits:
- Transparency: Gain transparency into your model's decision-making process by understanding the significance of each signal.
- Optimization: Identify and focus on the most influential features to optimize your model and enhance its predictive accuracy.
- Decision support: Make more informed decisions by leveraging insights into the factors driving your model's predictions.
- Model debugging: Pinpoint potential issues or biases by closely examining the importance scores of different features.
- Enhanced explainability: Communicate model behavior more effectively to stakeholders and build trust in your risk decision-making.
Updated 3 months ago