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86
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FIMI
2003
170views Data Mining» more  FIMI 2003»
14 years 11 months ago
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
74
Voted
NIPS
2003
14 years 11 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
CN
2006
110views more  CN 2006»
14 years 9 months ago
Maximal lifetime scheduling for K to 1 sensor-target surveillance networks
This paper addresses the maximal lifetime scheduling for k to 1 sensor
Hai Liu, Peng-Jun Wan, Xiaohua Jia
DCG
2006
96views more  DCG 2006»
14 years 9 months ago
k-Sets, Convex Quadrilaterals, and the Rectilinear Crossing Number of Kn
We use circular sequences to give an improved lower bound on the minimum number of ( k)
József Balogh, Gelasio Salazar
JSS
2008
157views more  JSS 2008»
14 years 9 months ago
Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...