#ai # [[Epistemic status]] #shower-thought #to-digest # Changelog ```dataview TABLE WITHOUT ID file.mtime AS "Last Modified" FROM [[#]] SORT file.mtime DESC LIMIT 3 ``` # Related # TODO > [!TODO] TODO # Active learning >"Membership Query Synthesis: This is where the learner generates its own instance from an underlying natural distribution. For example, if the dataset are pictures of humans and animals, the learner could send a clipped image of a leg to the teacher and query if this appendage belongs to an animal or human. This is particularly useful if the dataset is small. Pool-Based Sampling: In this scenario, instances are drawn from the entire data pool and assigned a confidence score, a measurement of how well the learner “understands” the data. The system then selects the instances for which it is the least confident and queries the teacher for the labels. Stream-Based Selective Sampling: Here, each unlabeled data point is examined one at a time with the machine evaluating the informativeness of each item against its query parameters. The learner decides for itself whether to assign a label or query the teacher for each datapoint." (Uncertainty sampling, Active Learning (Machine Learning) - Wikipedia) > # External links