The model interpretation dashboard is primarily used in the areas of artificial intelligence, big data, smart data and digital transformation. When companies use machine learning or AI models, the results are often difficult to understand. This is where a model interpretation dashboard can help: it is a user-friendly tool that makes the "black box" behind AI decisions visible.
The dashboard presents the most important information in an understandable way, for example which factors have influenced a result and how strong their influence was. This means that even people without a technical background can understand why a model makes certain predictions - for example, why a customer is granted or rejected a loan.
An illustrative example: a bank uses AI to assess credit risks. In the model interpretation dashboard, decision-makers can see at a glance that income and repayment history have played the biggest role. The dashboard thus ensures greater transparency, promotes trust in AI solutions and supports better, more comprehensible decisions.
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