5463 search results - page 18 / 1093 » Evaluating algorithms that learn from data streams |
KDD
2005
ACM
15 years 3 months ago
2005
ACM
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
104
Voted
DASFAA
2006
IEEE
15 years 4 months ago
2006
IEEE
Abstract. In emerging data stream applications, data sources are typically distributed. Evaluating multi-join queries over streams from different sources may incur large communica...
129
Voted
CVPR
2009
IEEE
16 years 5 months ago
2009
IEEE
Multi-instance multi-label learning (MIML) refers to the
learning problems where each example is represented by a
bag/collection of instances and is labeled by multiple labels.
...
NIPS
1998
14 years 11 months ago
1998
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
65
Voted
AI
2001
Springer
15 years 2 months ago
2001
Springer
We present our experience in applying a rule induction technique to an extremely imbalanced pharmaceutical data set. We focus on using a variety of performance measures to evaluate...