When several items are grouped, which type of machine learning algorithm can determine which items in the group predict the presence of other items?

The machine learning algorithm that can determine which items in a group predict the presence of other items is called Association. Association rule mining is a type of unsupervised learning technique used to discover interesting relationships, associations or correlations between variables in large datasets. It involves identifying frequently occurring patterns or itemsets in a dataset and using these patterns to predict the likelihood of the occurrence of other items. In the context of grouping items, association rule mining can be used to identify which items tend to appear together, and to predict the presence of certain items based on the presence of others.