The document presents a method for automatic demonstration and feature selection for robot learning. It describes an experiment where a robot learns a task from user demonstrations of placing a green object on a red object. The method, called Dissimilarity Mapping Filtering (DMF), is able to correctly select the relevant demonstrations and features for the task. It identifies the last two demonstrations as incorrect and discards features related to the initial position of the green object as irrelevant. The results validate that DMF can accurately perform demonstration and feature selection to support robot learning.