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173
Voted
KDD
1998
ACM
141views Data Mining» more  KDD 1998»
15 years 9 months ago
Rule Discovery from Time Series
We consider the problem of nding rules relating patterns in a time series to other patterns in that series, or patterns in one series to patterns in another series. A simple examp...
Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Ren...
KDD
1994
ACM
117views Data Mining» more  KDD 1994»
15 years 9 months ago
Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges
We applied TETRAD II, a causal discovery program developed in Carnegie Mellon University's Department of Philosophy, to a database containing information on 204 U.S. colleges...
Marek J. Druzdze, Clark Glymour
192
Voted
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 9 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
15 years 9 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
KDD
2010
ACM
215views Data Mining» more  KDD 2010»
15 years 9 months ago
On the quality of inferring interests from social neighbors
This paper intends to provide some insights of a scientific problem: how likely one’s interests can be inferred from his/her social connections – friends, friends’ friends,...
Zhen Wen, Ching-Yung Lin
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