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» Using Anonymized Data for Classification
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111
Voted
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 2 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
110
Voted
ENGL
2007
191views more  ENGL 2007»
15 years 2 months ago
Data Mining for extraction of fuzzy IF-THEN rules using Mamdani and Takagi-Sugeno-Kang FIS
— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
CHI
2005
ACM
16 years 2 months ago
Giving the caller the finger: collaborative responsibility for cellphone interruptions
We present a system in which a cell phone decides whether to ring by accepting votes from the others in a conversation with the called party. When a call comes in, the phone first...
Stefan Marti, Chris Schmandt
109
Voted
CSCW
2010
ACM
15 years 11 months ago
Warrants and deception in computer mediated communication
This article explores the operation of warrants, connections between online and real-world identities, on deceptive behavior in computer-mediated communication. A survey of 132 pa...
Darcy Warkentin, Michael Woodworth, Jeffrey T. Han...
123
Voted
ICML
2007
IEEE
16 years 3 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...