Tips, tricks, and comments related to topics in data science and machine learning. Used to be called "data mining and predictive analytics" but updated the title to reflect the language of the day!
Hosted by Dean Abbott, Abbott Analytics
KDNuggets has a new poll on whether or not "data mining" should still be used to describe the kind of analysis we all know and love. It is still barely winning, but interesting, Knowledge Discovery is almost beating it out as the better term.
I read somewhere where the mining analogy breaks down for some kinds of mining, e.g., where the treasure is scarce (the "nugget") and the other material is not ("plain rock").
This argument, of course, is that data mining is like this kind of mining ("scarce treasure in dross material"), but the name is wrong since "data miners" mine for insight (potential knowledge)--not data.
In other kinds of mining (coal, oil?), only the scope of the problem may change. The treasure is plentiful (where it is), but you still have to find it midst all those acres.
I voted for "Knowledge Discovery" in this poll.
ReplyDeleteI read somewhere where the mining analogy breaks down for some kinds of mining, e.g., where the treasure is scarce (the "nugget") and the other material is not ("plain rock").
This argument, of course, is that data mining is like this kind of mining ("scarce treasure in dross material"), but the name is wrong since "data miners" mine for insight (potential knowledge)--not data.
In other kinds of mining (coal, oil?), only the scope of the problem may change. The treasure is plentiful (where it is), but you still have to find it midst all those acres.
Van Scott