Model

• A model learns from training data if its performance improves after data is taken into account.
• A model is said to overfit if it performs well on training data but poorly on unseen data.
• On the other hand, a model is said to underfit if it performs poorly on both training and unseen data.

Process

A training feeds a learning algorithm. The learning algorithm then produces a function that maps the input to the output. The function is the model. The model takes an input feature and outputs a prediction.