Data Stream Mining - COMPX523 (2020)
Data streams are everywhere, from F1 racing over electricity networks to news feeds. Data stream mining relies on and develops new incremental algorithms that process streams under strict resource limitations.
Paper Information
| Points: | 15.0 |
|---|---|
| Prerequisite(s): | COMPX305 or COMPX310 or COMP316 or COMP321 and a further 30 points at 300 level in Computer Science |
| Internal assessment / examination: | 100:0 |
| Restriction(s): | COMP423, COMP523 |
Trimesters and Locations
| Occurrence Code | When taught | Where taught |
|---|---|---|
| 20A (HAM) | A Trimester : 2 Mar 2020 - 28 Jun 2020 | Hamilton |
Timetabled Lectures
The Timetable for 2020 is not available.
Indicative Fees for Data Stream Mining (COMPX523)
| Occurrence | Domestic | International | |
|---|---|---|---|
| Tuition | Resource | ||
| 20A (HAM) | $1052 | $4293 | |
Paper Outlines for Data Stream Mining (COMPX523)
The following paper outlines are available for Data Stream Mining (COMPX523).
If your paper occurrence is not listed contact the Faculty or School office.
Additional Information
Available Subjects: Computer Science | Electrical and Electronic Engineering | Electronic Engineering | Software Engineering
Other available years: Machine Learning for Data Streams - COMPX523 (2024) , Data Stream Mining - COMPX523 (2023) , Data Stream Mining - COMPX523 (2022) , Data Stream Mining - COMPX523 (2021) , Data Stream Mining - COMPX523 (2019)
Paper details current as of : 29 November 2023 7:52pm
Indicative fees current as of : 30 November 2023 4:32am