Sciweavers

Share
28 search results - page 1 / 6
» Making Time-Series Classification More Accurate Using Learne...
Sort
View
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
12 years 1 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
ICML
2006
IEEE
13 years 17 days ago
Fast time series classification using numerosity reduction
Many algorithms have been proposed for the problem of time series classification. However, it is clear that one-nearest-neighbor with Dynamic Time Warping (DTW) distance is except...
Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton...
AI
1998
Springer
12 years 4 months ago
ELEM2: A Learning System for More Accurate Classifications
We present ELEM2, a new method for inducing classification rules from a set of examples. The method employs several new strategies in the induction and classification processes to ...
Aijun An, Nick Cercone
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
11 years 9 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki
SIGIR
2008
ACM
11 years 11 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
books