| Poll |
Which of the following Data Mining (DM) topics are most important for your work or research? (Choose top 3) [113 voters]
|
| Scaling up DM algorithms for huge data (46) |
41% |
| Mining text (33) |
29% |
| Automating data cleaning (30) |
27% |
| Dealing with unbalanced and cost-sensitive data (29) |
26% |
| Mining data streams (20) |
18% |
| Mining links and networks (19) |
17% |
| Unified theory of DM (18) |
16% |
| DM for biological problems (16) |
14% |
| DM with privacy (10) |
8.9% |
| Mining images (8) |
7.1% |
| DM for security applications (6) |
5.4% |
| Distributed (multi-agent) DM (4) |
3.6% |
| Other (21) |
8% |
|
Comments
Editor, Cost-sensitive data
By "Cost-sensitive" data I mean data
which has different cost to get it.
E.g. for a medical diagnosis, we can use
data from a blood test or a spinal fluid test,
but blood test is much cheaper (and easier) to
get than a spinal fluid test.
Making decision in such cases (which is really
all the real-world cases) requires combining
accuracy and other metrics with the cost of getting
the data.
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