2884 search results - page 47 / 577 » Evaluating learning algorithms and classifiers |
145
Voted
COLT
1998
Springer
15 years 8 months ago
1998
Springer
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
117
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KDD
2009
ACM
16 years 4 months ago
2009
ACM
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
113
Voted
ICTAI
2008
IEEE
15 years 10 months ago
2008
IEEE
It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
144
Voted
ALGORITHMICA
2006
15 years 4 months ago
2006
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
120
Voted
AUSAI
2006
Springer
15 years 7 months ago
2006
Springer
Attribute subsetting is a meta-classification technique, based on learning multiple base-level classifiers on projections of the training data. In prior work with nearest-neighbour...