Running_var in Machine Learning: Understanding Moving Variance for Batch Normalization

'Running_var' in machine learning is a method used to calculate the variance of each node's output in a neural network, also known as moving variance. It's calculated during the training process and dynamically updates the variance of each node's output, helping the network better adapt to different data distributions. In deep learning, 'running_var' is commonly used in the Batch Normalization (BN) operation, a key optimization technique.