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» Evaluating algorithms that learn from data streams
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KDD
1998
ACM
106views Data Mining» more  KDD 1998»
15 years 4 months ago
Simultaneous Reliability Evaluation of Generality and Accuracy for Rule Discovery in Databases
This paper presents an algorithm for discovering conjunction rules with high reliability from data sets. The discovery of conjunction rules, each of which is a restricted form of ...
Einoshin Suzuki
192
Voted
VLDB
2004
ACM
112views Database» more  VLDB 2004»
16 years 24 days ago
Tracking set-expression cardinalities over continuous update streams
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources. In i...
Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastog...
179
Voted
PRL
2011
14 years 3 months ago
A Bayes-true data generator for evaluation of supervised and unsupervised learning methods
Benchmarking pattern recognition, machine learning and data mining methods commonly relies on real-world data sets. However, there are some disadvantages in using real-world data....
Janick V. Frasch, Aleksander Lodwich, Faisal Shafa...
KDD
2005
ACM
151views Data Mining» more  KDD 2005»
16 years 29 days ago
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Qiaozhu Mei, ChengXiang Zhai
110
Voted
ICDM
2005
IEEE
122views Data Mining» more  ICDM 2005»
15 years 6 months ago
Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation Trees
In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
Kun Zhang, Zujia Xu, Jing Peng, Bill P. Buckles