What is loss function tuning in machine learning?

What is loss function tuning in machine learning?

Loss function tuning refers to the process of adjusting the loss function used in training machine learning models to improve their performance.

Why is it important to tune the loss function?

Tuning the loss function is crucial because it directly impacts how well the model learns from the data and generalizes to new data.

Can you give me an example of a loss function?

Sure! A common example is the Mean Squared Error (MSE), which measures the average squared difference between predicted and actual values.

How do I know if my loss function is well-tuned?

You can assess the tuning by monitoring the training and validation loss; they should decrease and converge without significant overfitting.