Difference between revisions of "EDA-DR-Concepts"
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+ | == Notes == | ||
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Latest revision as of 09:27, 25 September 2020
Concepts of Dimension Reduction
(Concepts of Dimension Reduction)
Abstract:
This unit discusses the "curse of dimensionality" in data mining, and introduces ideas and strategies how dimension reduction can address this problem in bioinformatics. Also: dimension reduction to create features for machine learning.
Objectives: |
Outcomes: |
Deliverables:
Prerequisites:
This page is only a stub; it is here as a placeholder to establish the logical framework of the site but there is no significant content as yet. Do not work with this material until it is updated to "live" status.
Evaluation
Evaluation: NA
Contents
Task:
- Read the introductory notes on dimension reduction and related methods for exploratory data analysis.
Self-evaluation
Further reading, links and resources
Notes
About ...
Author:
- Boris Steipe <boris.steipe@utoronto.ca>
Created:
- 2017-09-17
Modified:
- 2017-09-18
Version:
- 0.1
Version history:
- 0.1 First stub
This copyrighted material is licensed under a Creative Commons Attribution 4.0 International License. Follow the link to learn more.
This page is only a stub; it is here as a placeholder to establish the logical framework of the site but there is no significant content as yet. Do not work with this material until it is updated to "live" status.