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GenIQ-Parkinson's
Law:
The GenIQ Model Expands to Fill the Time Available for Model Completion Bruce Ratner, Ph.D.
Parkinson's Law states
that "work expands to fill the time available for its completion." It
was first articulated by C. Northcote Parkinson in the book Parkinson's
Law: The Pursuit of Progress, (London, John Murray, 1958) based on
extensive experience in the British Civil Service. The scientific
observations which contributed to the law's development included noting
that as Britain's overseas empire declined in importance, the number of
employees at the Colonial Office increased.
I propose the
GenIQ-Parkinson's Law that states "The GenIQ Model expands to fill the
time available for model completion - guaranteeing the best model for
the allotted time." The GenIQ modeling process is evolutionary; thus,
it theoretically never stops, similar to human evolution. Unlike for
mankind and womankind, there is a stopping rule (addition to various
empirical ones) for GenIQ model development: "time is up." The required
GenIQ Model for a given amount of time is the "best" model among all
models via other methods for a given amount of time. GenIQ can deliver
the best model for the time available, as a direct consequence of its
evolutionary paradigm and unique optimization of the decile analysis.
This is an unparallel feature of the GenIQ Model that alternative
methods can not offer. Statistical techniques like the logistic and
ordinary least-squares regression models require time-consuming data
preparation that sets the data analyst's actual start-time for model
building after days of data preparation. GenIQ requires no data
preparation, only 1] to insure there are no impossible or improbable
values (e.g., age of 120 years, or a boy named Sue, respectively), and
2] to audit missing and zero values. The GenIQ-Parkinson's Laws is
appropriate for situations when there is limited amount of time to
build a model, because without a time restriction there is an equal
playing field for all modeling techniques.
For a free-n-easy discussion of The GenIQ Model click here. |
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