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» Evaluating learning algorithms and classifiers
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BMCBI
2008
219views more  BMCBI 2008»
15 years 20 days ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
149
Voted
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 29 days ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
TASLP
2008
131views more  TASLP 2008»
15 years 14 days ago
A Noise-Robust FFT-Based Auditory Spectrum With Application in Audio Classification
In this paper, we investigate the noise robustness of Wang and Shamma's early auditory (EA) model for the calculation of an auditory spectrum in audio classification applicati...
Wei Chu, B. Champagne
148
Voted
MOBISYS
2009
ACM
16 years 1 months ago
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sen...
Hong Lu, Wei Pan, Nicholas D. Lane, Tanzeem Choudh...
81
Voted
ICML
2005
IEEE
16 years 1 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Thomas Finley, Thorsten Joachims