[Haskell-cafe] data mining, or something like it
mjt464 at gmail.com
Tue May 30 06:57:44 UTC 2017
I can't help you with an up to date data mining definition, but it sounds
like you're in the ball park.
Regarding your musical plans, try: http://donyaquick.com/kulitta/
And I think Paul Hudak did work in that general area years ago too, perhaps
On 30 May 2017 2:53 pm, "Dennis Raddle" <dennis.raddle at gmail.com> wrote:
> I have a general computer science question first, and then I will ask if
> Haskell might be helpful for this.
> I'm researching "algorithmic music composition," the construction of
> musical compositions through choices made my algorithms. No piece of music
> is ever 100% human-composed or 100% algorithmic -- so to be more clear, I'm
> interested in researching "musical fitness functions" that produce good
> results when searching the music space. Anything the computer composes will
> be listened to by me, and only the most promising fitness functions will be
> explored in greater depth.
> So my general question is about the following idea --
> So in the course of generating lots of musical examples, and rating them
> as "good" or "bad," I'll end up with a database that can perhaps be "mined"
> for new fitness functions. I would start with a question. A random example
> of a question would be "is there a pattern in the density of dissonance,
> such that more dissonance in certain places in the composition tends to
> make it better (or worse)?" I would suspect, out of pure intuition, that it
> does, but I may not know the exact details. For instance, I might not know
> if dissonance matters more in certain places within a measure. So I could
> code up something that looks for patterns among the good and bad musical
> examples in my database to see if it can find something specific.
> So is this called "data mining" or something else?
> Second, are there any Haskell libraries that can help with this task?
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