Matt Dillon
Semolina comes from wheat
Girls like that is why dudes like Perry never get laid.
Measure 114 is unconstitutional.
It is obvious that Dutch has never shot a gun. He's just making shit up like usual.
Girls like that is why dudes like Perry never get laid.
Wow, you got life fucked up. You extrapolated all of that from the ether. Weirdo.
I don't believe you.
I understand and agree but..................
No, that's likely how it is done. How would YOU use software to find the authorship of a work?
It's pretty straightforward but requires a lot of compute resources.
No, that's likely how it is done. How would YOU use software to find the authorship of a work?
It's pretty straightforward but requires a lot of compute resources.
You can keep your meth-mouth trailer ladies, Matt. I know that's what you like. Gettin' to "nail 'er in 'er trailer" like the song says.
I don't care.
No, that's likely how it is done. How would YOU use software to find the authorship of a work?
It's pretty straightforward but requires a lot of compute resources.
Still trying to make up shit, eh?
You've never programmed anything in your life, ever.
Just have to look for similarities, dumbass. Kinda like you and @LurchAddams.
Still trying to make up shit, eh? You're not even a competent programmer.
Lie.
I will freely admit that programming is not my strong suit. That's why it was always a lot of work for me to write up the Python and R programs for processing the data for text analytics. I just recently found Orange which is a much nicer graphical method for building text analytics (and other data mining applications).
That's what I was talking about. "Similarities" between authorship can be dealt with mathematically. The field of text analytics is really kinda neat.
Fiction.NOt at all. I actually spent a couple years learning text analytics.
I don't care about your Holy Links. Looking shit up on Google proves nothing.That's one of the ways. Here, you can read about some of the "distance measures" here:
You deny and discard statistical math.It's actually some really cool math.
Buzzword fallacies.Once you are able to create the term-document matrix (or it's inverse the document-term matrix) you have a kind of multidimensional vector.
All you are showing is that you don't know how to program a computer as well as denying and discarding statistical math.And then all you need to do is treat it that way. Sure there's more to it than simple "distance metrics" but distances and clustering analyses are great ways to determine authorship.
I will freely admit that programming is not my strong suit. That's why it was always a lot of work for me to write up the Python and R programs for processing the data for text analytics. I just recently found Orange which is a much nicer graphical method for building text analytics (and other data mining applications).
That's what I was talking about. "Similarities" between authorship can be dealt with mathematically. The field of text analytics is really kinda neat.