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EPIA
2003
Springer
14 years 24 days ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
VISUALIZATION
1998
IEEE
13 years 11 months ago
A general method for preserving attribute values on simplified meshes
Many sophisticated solutions have been proposed to reduce the geometric complexity of 3D meshes. A less studied problem is how to preserve on a simplified mesh the detail (e.g. co...
Paolo Cignoni, Claudio Montani, Roberto Scopigno, ...
AIME
2003
Springer
14 years 24 days ago
Attribute Interactions in Medical Data Analysis
There is much empirical evidence about the success of naive Bayesian classification (NBC) in medical applications of attribute-based machine learning. NBC assumes conditional inde...
Aleks Jakulin, Ivan Bratko, Dragica Smrke, Janez D...
ICMLA
2003
13 years 9 months ago
Fast Class-Attribute Interdependence Maximization (CAIM) Discretization Algorithm
– Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an a...
Lukasz A. Kurgan, Krzysztof J. Cios
COLT
1999
Springer
13 years 12 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...