Adding to the previous comment by Dean Abbott, abo...

2008-05-18T01:57:00.000-07:00

Adding to the previous comment by Dean Abbott, about misconceptions of data mining.

As a long time practitioner of DM, in my view the DM algorithm has everything to do with the current inability to cease rare case scenarios. My DM model for example – GT data mining – can catch such cases. It can be done through a number of mechanisms: early detection of suspect's ground preparations, background, and typical camouflage pattern of behavior – to name a few.
There are other DM shortcomings that exist but not the ones mentioned in the article.

I don't understand what's the fuss about DM abilities, which are in effect, no more than a straight forward use of one's own data, the digestion and comprehension of operations data. That's the essence of TI data advantage.

I've always been somewhat puzzled as to why data m...

2007-04-28T21:19:00.000-07:00

I've always been somewhat puzzled as to why data mining in particular is singled out for extra scrutiny by Feingold. After reading older versions of bills sponsored by him a few years ago, I suspect that part of the problem is a lack of understanding of the distinctions between data mining and data joining (i.e., putting data together that shouldn't be put together for privacy reasons).

But it also seems to me that as long as the deployed system doesn't contain any data mining models, they escape the scrutiny. Is that so? For example, if you built a series of decision trees and cherry-picked some rules, built your own expert system from these rules, you aren't actually using "data mining" in the final model. In that case, data mining technology didn't determine whether a particular pattern is indicative of criminal activity, but rather a business rule is.

It also seems to me that whether the rule was developed by a "data mining" algorithm or someone's experience is irrelevant. What Feingold should pursue is not data mining but validation: how does one determine that a model or a rule is valid? Simulation...resamping...theory...a ll of these.

Thanks for your blog by the way--it is fascinating and an important contribution to the data mining community.

Comments on Crime Analysis and Data Mining: Data Mining turns Political!

Adding to the previous comment by Dean Abbott, abo...

I've always been somewhat puzzled as to why data m...