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» Evaluating algorithms that learn from data streams
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GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
16 years 2 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
KDD
1998
ACM
131views Data Mining» more  KDD 1998»
15 years 11 months ago
Interestingness-Based Interval Merger for Numeric Association Rules
We present an algorithm for mining association rules from relational tables containing numeric and categorical attributes. The approach is to merge adjacent intervals of numeric v...
Ke Wang, Soon Hock William Tay, Bing Liu
JMLR
2006
99views more  JMLR 2006»
15 years 7 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
ECSQARU
2001
Springer
16 years 3 days ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse
WEBDB
2009
Springer
131views Database» more  WEBDB 2009»
16 years 2 months ago
Functional Dependency Generation and Applications in Pay-As-You-Go Data Integration Systems
Recently, the opportunity of extracting structured data from the Web has been identified by a number of research projects. One such example is that millions of relational-style H...
Daisy Zhe Wang, Xin Luna Dong, Anish Das Sarma, Mi...