22. Solution: Pooling Intuition

Solution

The correct answer is decrease the size of the output and prevent overfitting . Preventing overfitting is a consequence of reducing the output size, which in turn, reduces the number of parameters in future layers.

Recently, pooling layers have fallen out of favor. Some reasons are:

• Recent datasets are so big and complex we're more concerned about underfitting.
• Dropout is a much better regularizer.
• Pooling results in a loss of information. Think about the max pooling operation as an example. We only keep the largest of n numbers, thereby disregarding n-1 numbers completely.