692 search results - page 7 / 139 » Why Experimentation can be better than |
107
Voted
MCS
2000
Springer
15 years 1 months ago
2000
Springer
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
66
Voted
SYNTHESE
2008
14 years 9 months ago
2008
Various formally valid counterexamples have been adduced against the Humean dictum that one cannot derive an "ought" from an "is." There are formal rebuttals--s...
AAAI
1998
14 years 11 months ago
1998
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
An algorithm independent metric is introduced that measures the dispersion of a uniform random sample drawn from the top ranked percentiles of the search space. A low dispersion f...
SIGIR
2012
ACM
12 years 12 months ago
2012
ACM
We give a fresh look into score normalization for merging result-lists, isolating the problem from other components. We focus on three of the simplest, practical, and widelyused l...