I have two different mathematical models I use to predict the dollar amount in claims a group will incur over the course of a year. I want to visually juxtapose how accurate those two models are on historical data (i.e. I know what actual claims for each group are) with group-level granularity. I haven't done much with data visualization in the past, so I was wondering if there are any pre-existing data-visualization paradigms that this kind of thing might fit into. Thanks.
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If you have a time series I guess plotting actual vs. predicted values in a graph would work fine. Maybe throw in the MAPE and adjusted R^2 as single values in one of the corners.
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In general before approaching any visualization you can use these links to understand more about what kind of data visualization you would need -
https://blog.hubspot.com/marketing/types-of-graphs-for-data-visualization https://www.datapine.com/blog/how-to-choose-the-right-data-visualization-types/
Now, as you have a date field (year), a numerical field (claims) which you want to show for different groups (categorical data) and you have output of two models and a actual values. ( so 3 different sources) .
Considering this you can create a line chart with time based data on x axis and claims on the y axis. The claims value can be shown based on the sources(historical data, model 1 and model 2) for comparison and you can provide a filter which will serve as a filter for groups.
This concept I just shared can be easily done in Tableau and you can see yourself.
