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» Evaluating algorithms that learn from data streams
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121
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ENC
2004
IEEE
15 years 4 months ago
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
A method to induce bayesian networks from data to overcome some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evalua...
Manuel Martínez-Morales, Ramiro Garza-Dom&i...
88
Voted
COLT
2005
Springer
15 years 2 months ago
Data Dependent Concentration Bounds for Sequential Prediction Algorithms
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
Tong Zhang
SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
15 years 2 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 6 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
190
Voted
ICDE
2007
IEEE
148views Database» more  ICDE 2007»
16 years 2 months ago
Conquering the Divide: Continuous Clustering of Distributed Data Streams
Data is often collected over a distributed network, but in many cases, is so voluminous that it is impractical and undesirable to collect it in a central location. Instead, we mus...
Graham Cormode, S. Muthukrishnan, Wei Zhuang