Overfitting and underfitting: Finding the right balance When training a ML model, a frequent struggle is finding that sweet spot between overfitting and underfitting.

Both overfitting and underfitting the data lead to model failure. The model can no longer handle new data and cannot be used for a soft sensor. The concepts of overfitting and underfitting data are ...

What Can Cause Overfitting? In some ways, overfitting stems from issues with how the original data model was built, creating gaps in the machine’s understanding. This can happen for many reasons — ...

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