Overfitting occurs when the model was so well trained that it fits the training data too perfectly and cannot handle new data.
Say you have a unique predictor of an outcome and that the data follows a quadratic pattern:
- You fit a linear regression on that data
, the predictions are weak. Your model is underfitting the data. There is a high error level on both the training error and the validation dataset. - You add the square of the predictor in the model
and find that your model makes good predictions. The error on both the training ...
