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Aggregation techniques: Difference between revisions

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# [[Other possible algorithms for calculating binary predicates|An analysis of these methods and simple weighted averaging]]
# [[Other possible algorithms for calculating binary predicates|An analysis of these methods and simple weighted averaging]]
# [[Trust-weighted histograms|Trust-weighted histograms]]
# [[Trust-weighted histograms|Trust-weighted histograms]]
# [[Trust/Probability/Population graphs algorithm|Trust/Probability/Population graphs algorithm]]
# [[Binned and continuous distributions|Binned and continuous distributions]]
# [[Binned and continuous distributions|Binned and continuous distributions]]
# [[Population distributions and graphical output with privacy|Population distributions and graphical output with privacy]]
# [[Population distributions and graphical output with privacy|Population distributions and graphical output with privacy]]

Revision as of 21:32, 30 August 2024

Main article: Technical overview of the ratings system

Aggregation refers to the way we combine the opinions of others to obtain a final value of the opinion. A poll which takes the sum of each person's candidate preference in an election and then calculates the percentage for each candidate is an aggregation technique.

A number of aggregation techniques are possible. A few are listed here:

  1. Bayes' equation with a simple example of its use.
  2. Simple averaging and a privacy enhancing variant thereof.
  3. Trust weighted averaging
  4. An analysis of these methods and simple weighted averaging
  5. Trust-weighted histograms
  6. Trust/Probability/Population graphs algorithm
  7. Binned and continuous distributions
  8. Population distributions and graphical output with privacy