Re^2: Extensive List of Names by Gender?

Thank you for your opinion.

*Just LONG*
I firmly believe that this is a reasonable question. Why else would CPAN host a module that attempts to solve this?

While I completely understand the limitations (The ambiguity of particular names for instance, as you pointed out) of a concept like this and I would never expect it to be 100% accurate, we target our audience through certain advertisements and offers based upon their gender. Would you ask a female if they wanted to buy * enhancement supplements? Would you ask a male if he wanted to buy a diaphragm?

As it just so happens, however, individuals are very unlikely to fill out a question that asks them "What gender are you?" and such questions must forever remain optional and 'skip-able'.

Therefore, our ability to unfailingly gather pointed data from our viewers is quite limited and we are attempting a 'behind-the-scenes' approach.

Subjective - I fail to see how you draw that conclusion as my feelings and opinion have very little to do with this.

Unreliable - Hypothetically. In its current form; however, this module produces 6.8% accuracy for our data. I am not asking for 100% accuracy, but I would like to see that number increase.

Finally, we anticipate that some of this data will end up being UNDEF which is perfectly acceptable.

This question that would not be 'touched with a 20 foot pole' was blatantly beaten with a one inch subjective metal bar.

Comment on Re^2: Extensive List of Names by Gender?

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Re^3: Extensive List of Names by Gender? by kennethk (Abbot) on Jul 12, 2013 at 18:37 UTC
#LONG:# Why else would CPAN host a module that attempts to solve this? Have you perused the CPAN Acme offerings? we target our audience through certain advertisements By providing context, you have very substantially informed the question. One of the points raised in the Slashdot discussion (And I am, of course, loathe to consider Slashdot as a reliable source) is that application dictates what you actually mean by gender in a CS context. And your targeting question is precisely why the real question here is what are your failure tolerances? What is the cost benefit of an incorrectly targeted ad vs. offering non-specific ads to the same consumer? Therefore, our ability to unfailingly gather pointed data from our viewers is quite limited and we are attempting a 'behind-the-scenes' approach. Which hits on the DB question: why are you doing this in preprocessing rather than post? You are applying a model to your data, and therefore potentially corrupting your input stream by mixing original and derived information. this module produces 6.8% accuracy for our data You do get that there is inherent error, which is important, however, 6.8% accuracy is a pretty specific number. How did you determine that? Do you have independent training and test data sets, or does that mean some guy looked at the results and guessed yes or no? #SHORT(ish):# Subjective means that there is no general right answer. Because the cost benefit questions are use case specific, you must tune your own list. Because you were asking about using someone else's list. Unreliable means you can't rely on an external answer. Because you were asking about using someone else's list. frozenwithjoy's dataset will give you what you need to generate your own list. You can set your tolerances where ever you like, and have quantified reliability metrics in a particular market. My whole point was not that you shouldn't do it; rather that someone else's solution is almost assuredly wrong for you, a.k.a. Does Not (yet) Exist. #11929 First ask yourself `How would I do this without a computer?' Then have the computer do it the same way.	[reply]

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Re^3: Extensive List of Names by Gender?
by kennethk (Abbot) on Jul 12, 2013 at 18:37 UTC

Why else would CPAN host a module that attempts to solve this?

Acme

we target our audience through certain advertisements

Therefore, our ability to unfailingly gather pointed data from our viewers is quite limited and we are attempting a 'behind-the-scenes' approach.

this module produces 6.8% accuracy for our data

#SHORT(ish):#

Subjective means that there is no general right answer. Because the cost benefit questions are use case specific, you must tune your own list. Because you were asking about using someone else's list.

Unreliable means you can't rely on an external answer. Because you were asking about using someone else's list.

frozenwithjoy's dataset will give you what you need to generate your own list. You can set your tolerances where ever you like, and have quantified reliability metrics in a particular market. My whole point was not that you shouldn't do it; rather that someone else's solution is almost assuredly wrong for you, a.k.a. Does Not (yet) Exist.

#11929 First ask yourself `How would I do this without a computer?' Then have the computer do it the same way.

[reply]