165 search results - page 15 / 33 » Algorithms for Sparse Linear Classifiers in the Massive Data... |
CORR
2007
Springer
13 years 7 months ago
2007
Springer
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
ML
2002
ACM
13 years 7 months ago
2002
ACM
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
FLAIRS
2008
13 years 9 months ago
2008
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
CINQ
2004
Springer
14 years 23 days ago
2004
Springer
Abstract. Data mining algorithms such as the Apriori method for finding frequent sets in sparse binary data can be used for efficient computation of a large number of summaries fr...