ylisovittamista
Ylisovittamista is a Finnish term that translates to "overfitting" in English. It is a concept commonly encountered in statistics and machine learning. Overfitting occurs when a statistical model learns the training data too well, to the point that it captures the noise and random fluctuations in the data rather than the underlying general patterns. This leads to a model that performs very well on the data it was trained on but poorly on new, unseen data.
The problem of overfitting arises when a model is too complex relative to the amount of data
To combat overfitting, several techniques are employed. These include using simpler models, collecting more training data,