What is Active Sampling in Machine Learning?
Active Sampling is a technique used in
machine learning and data acquisition, where the model actively selects or samples new data points to be labeled or added to the training set. Active sampling aims to prioritize informative or uncertain samples that will contribute most to improving the model's performance.
