Why More Samples Improve Accuracy

Industrial processes have natural variability. More samples help the model learn the full range of behavior:

  • Normal operating range
  • Rare events and process upsets
  • Sensor drift over time
  • Background noise patterns
  • Non-linear zones at extremes
Recommended sample counts:
  • Minimum: 30 samples
  • Good: 50 samples
  • Ideal: 70+ samples (especially for 6+ variable models)
The system shows a warning banner when data is below the minimum threshold for reliable predictions.
Try it in the app
Try: In IoT Simulation mode, start a simulation and watch R² improve in real-time as more rows are collected. Notice how predictions stabilize beyond the 30-row mark.
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