Category: Data

Daragh Sibley, et al, discuss using genetic algorithms to help design clothing:

Recombination. Having selected a set of high performing blouses we can now consider how they should be recombined to form a new child. While a traditional genetic algorithm would stochastically search all combinations over many market generations, we can shortcut that process by algorithmically looking for features that have been historically preferred by our target client segment.

To achieve this, we find statistical regularities between the population of blouses’ attributes (or configurations of attributes) and client feedback. For instance, we can model the relationship between attributes of our existing blouses and client feedback via:

Genetic algorithms (and Koza-style genetic programming) have long been a favorite topic of mine.  Integrating GA with fashion was not something that came to mind, but is a very interesting solution.

Kenneth Fisher discusses methods for comparing table contents:

Roll your own
Ie write one T-SQL query to compare the structure of the two tables (this one will always be the same) and another to compare the data (new each time).

• Benefits

  • Free.
  • You get practice in writing T-SQL (yes, I’m stretching there.)

• Flaws

  • Can take quite a bit of time to write. (Don’t forget to check for NULLs separately.)

  • Mistakes happen.

  • Performance may not be spectacular.

Good comparison.  Check it out.