O'Reilly logo

Deep Learning By Example by Ahmed Menshawy

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Bias-variance decomposition

In the previous section, we knew how to select the best hyperparameters for our model. This set of best hyperparameters was chosen based on the measure of minimizing the cross validated error. Now, we need to see how the model will perform over the unseen data, or the so-called out-of-sample data, which refers to new data samples that haven't been seen during the model training phase.

Consider the following example: we have a data sample of size 10,000, and we are going to train the same model with different train set sizes and plot the test error at each step. For example, we are going to take out 1,000 as a test set and use the other 9,000 for training. So for the first training round, we will randomly select ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required