ylisovittuvuuteen
Ylisovittuvuuteen, a Finnish term, translates to "overfitting" in English and refers to a common problem in machine learning and statistical modeling. It occurs when a model learns the training data too well, to the point where it captures noise and random fluctuations in the data as if they were genuine patterns. This results in a model that performs exceptionally well on the data it was trained on, but poorly on new, unseen data.
The primary cause of overfitting is a model that is too complex relative to the amount of
Detecting overfitting typically involves splitting the data into training and testing sets. The model is trained
To combat overfitting, several techniques are employed. These include using simpler models, increasing the amount of