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  2. De-identification - Wikipedia

    en.wikipedia.org/wiki/De-identification

    A systematic review of fourteen distinct re-identification attacks found "a high re-identification rate […] dominated by small-scale studies on data that was not de-identified according to existing standards". [6] De-identification is adopted as one of the main approaches toward data privacy protection. [7]

  3. Identifiability - Wikipedia

    en.wikipedia.org/wiki/Identifiability

    Then this model is not identifiable, [4] only the product βσ² ∗ is (where σ² ∗ is the variance of the latent regressor x*). This is also an example of a set identifiable model: although the exact value of β cannot be learned, we can guarantee that it must lie somewhere in the interval ( β yx , 1÷ β xy ), where β yx is the ...

  4. Pseudonymization - Wikipedia

    en.wikipedia.org/wiki/Pseudonymization

    GDPR compliant pseudonymization not only enables greater privacy-respectful use of data in today's "big data" world of data sharing and combining, but it also enables data controllers and processors to reap explicit benefits under the GDPR for correctly pseudonymized data.The benefits of properly pseudonymized data are highlighted in multiple ...

  5. Number of crimes with no suspect identified ‘not acceptable ...

    www.aol.com/number-crimes-no-suspect-identified...

    The force failed to identify a suspect in a range of neighbourhood crimes in 166 areas in three years, Channel 4’s Dispatches reports.

  6. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  7. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    The following fallacies involve relations whose truth values are not guaranteed and therefore not guaranteed to yield true conclusions. Types of propositional fallacies: Affirming a disjunct – concluding that one disjunct of a logical disjunction must be false because the other disjunct is true; A or B; A, therefore not B .

  8. Parameter identification problem - Wikipedia

    en.wikipedia.org/wiki/Parameter_identification...

    Here both equations are identified if c and d are nonzero. Note that this is the structural form of the model, showing the relations between the Q and P. The reduced form however can be identified easily. Fisher points out that this problem is fundamental to the model, and not a matter of statistical estimation:

  9. List of commonly misused English words - Wikipedia

    en.wikipedia.org/wiki/List_of_commonly_misused...

    Non-standard: I could not fire because I did not have line-of-site to the target. stationary and stationery. Stationary is an adjective meaning "not moving"; stationery is a noun meaning office supplies. Standard: The train remained stationary for a few moments, before lurching forward along the track.