Stream Sampling with Immediate Decision
Bardia Panahbehagh, Rapha\"el Jauslin, Yves Till\'e

TL;DR
This paper presents a simple, efficient algorithm for immediate decision stream sampling that allows for random selection of units with equal or unequal probabilities, suitable for streaming data in real-time.
Contribution
It introduces a novel, straightforward method for immediate decision sampling applicable to both equal and unequal probability scenarios in streaming data.
Findings
Effective for real-time stream data sampling
Applicable to both equal and unequal probability sampling
Simple implementation with a single decision condition
Abstract
The manuscript introduces a method to select a random sample from a stream by deciding on each sampling unit immediately after observing it. The process could be applied to unequal as well as equal probability sampling. The implementation is straightforward. Algorithm selects a unit in the sample based on a single condition. It is particularly effective to make direct decisions on stream data, despite the data arriving in groups or the stream being linear.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Stream Mining Techniques · Machine Learning and Algorithms · Anomaly Detection Techniques and Applications
