Which type of visualization is most effective for showing trends in both accuracy and latency metrics for an AI model?

The dual-axis line chart is an effective visualization for showing trends in both accuracy and latency metrics for an AI model because it allows for the simultaneous representation of two different data sets that have distinct measurement units but are both crucial for evaluating model performance. By using two y-axes, one for accuracy and one for latency, it becomes easy to observe how these metrics change over time or across different conditions, allowing for a direct comparison and highlighting any trade-offs between them.

In this format, trends can be easily identified, enabling analysts to see whether improvements in accuracy might correspond with changes in latency, or if there are particular points in time or conditions where these metrics diverge significantly. This is particularly important in AI model evaluation, as both accuracy (a measure of correctness) and latency (a measure of responsiveness) provide critical insights into the model's performance and usability.

Other visualization options do not effectively serve this purpose. For instance, a pie chart is typically used for showing proportions of a whole and wouldn't convey trends over time. A stacked area chart accumulates values, which could complicate the interpretation of individual trends for both metrics. A box plot is designed to summarize the distribution of a single variable and compare groups rather than show trends over time, making it less