Single Precision and Performance

The CSA Prediction Engine uses float32 (single precision) as the default for numerical computations to balance speed and performance. While float64 (double precision) offers more accuracy, it requires more memory and computational resources. In high-demand scenarios, float32 reduces both the memory footprint and computation time, which is crucial for handling large datasets and maintaining API responsiveness. However, this precision is typically sufficient for most predictive analytics tasks.

Given the precision of float32, users should evaluate results only up to six decimal places to avoid unnecessary precision loss. This is sufficient for most predictive models and maintains the efficiency and speed benefits of using float32.