Overfitting vs Underfitting Machine Learning


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Maxpooling vs minpooling vs average pooling

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Pooling is performed in neural networks to reduce variance and computation complexity. Many times, beginners blindly use a pooling method without knowing the reason for using it. Here is a comparison of three basic pooling methods that are widely used. The three types of pooling operations are: Max pooling: The maximum pixel value of the batch is selected. Min pooling: The minimum pixel value of the batch is selected. Average pooling: The average value of all the pixels in the batch is selected. The batch here means a group of pixels of size equal to the filter size which is decided based on the size of the image. In the following example, a filter of 9x9 is chosen. The output of the pooling method varies with the varying value of the filter size. The operations are illustrated through the following figures. Average, Max and Min pooling of size 9x9 applied on an image We cannot say that a particular pooling method is better over others generally. The choice of pooling operation is made...
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Generative AI - Prompting with purpose: The RACE framework for data analysis

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Best Practices for Storing and Loading JSON Objects from a Large SQL Server Table Using .NET Core

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