Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science
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Published By Springer Berlin Heidelberg

9783540734987, 9783540734994

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Data Selection Using SASH Trees for Support Vector Machines

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_22 ◽

2007 ◽

pp. 286-295 ◽

Cited By ~ 1

Author(s):

Chaofan Sun ◽

Ricardo Vilalta

Keyword(s):

Support Vector Machines ◽

Data Selection ◽

Support Vector ◽

Vector Machines

FIDS: Monitoring Frequent Items over Distributed Data Streams

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_35 ◽

2007 ◽

pp. 464-478 ◽

Cited By ~ 3

Author(s):

Robert Fuller ◽

Mehmed Kantardzic

Keyword(s):

Data Streams ◽

Distributed Data ◽

Distributed Data Streams ◽

Frequent Items

Outlier Detection with Kernel Density Functions

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_6 ◽

2007 ◽

pp. 61-75 ◽

Cited By ~ 60

Author(s):

Longin Jan Latecki ◽

Aleksandar Lazarevic ◽

Dragoljub Pokrajac

Keyword(s):

Outlier Detection ◽

Kernel Density ◽

Density Functions

A Unified View of Objective Interestingness Measures

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_40 ◽

2007 ◽

pp. 533-547 ◽

Cited By ~ 17

Author(s):

Céline Hébert ◽

Bruno Crémilleux

Keyword(s):

Interestingness Measures ◽

Unified View

Analyzing the Performance of Spam Filtering Methods When Dimensionality of Input Vector Changes

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_28 ◽

2007 ◽

pp. 364-378 ◽

Cited By ~ 2

Author(s):

J. R. Méndez ◽

B. Corzo ◽

D. Glez-Peña ◽

F. Fdez-Riverola ◽

F. Díaz

Keyword(s):

Input Vector ◽

Spam Filtering

Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_7 ◽

2007 ◽

pp. 76-90

Author(s):

Vincent Yan Fu Tan ◽

See-Kiong Ng

Keyword(s):

Data Mining ◽

Probability Density Function ◽

Probability Density ◽

Density Function ◽

Privacy Preserving ◽

Privacy Preserving Data Mining ◽

Function Reconstruction

Probabilistic Model for Structured Document Mapping

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_64 ◽

2007 ◽

pp. 854-867 ◽

Cited By ~ 2

Author(s):

Guillaume Wisniewski ◽

Francis Maes ◽

Ludovic Denoyer ◽

Patrick Gallinari

Keyword(s):

Probabilistic Model ◽

Structured Document

Categorizing Evolved CoreWar Warriors Using EM and Attribute Evaluation

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_51 ◽

2007 ◽

pp. 681-693

Author(s):

Doni Pracner ◽

Nenad Tomašev ◽

Miloš Radovanović ◽

Mirjana Ivanović

Keyword(s):

Attribute Evaluation

Distributed and Shared Memory Algorithm for Parallel Mining of Association Rules

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_27 ◽

2007 ◽

pp. 349-363 ◽

Cited By ~ 2

Author(s):

J. Hernández Palancar ◽

O. Fraxedas Tormo ◽

J. Festón Cárdenas ◽

R. Hernández León

Keyword(s):

Shared Memory ◽

Association Rules ◽

Parallel Mining

Evolving Committees of Support Vector Machines

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_20 ◽

2007 ◽

pp. 263-275 ◽

Cited By ~ 1

Author(s):

D. Valincius ◽

A. Verikas ◽

M. Bacauskiene ◽

A. Gelzinis

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Data Selection Using SASH Trees for Support Vector Machines

FIDS: Monitoring Frequent Items over Distributed Data Streams

Outlier Detection with Kernel Density Functions

A Unified View of Objective Interestingness Measures

Analyzing the Performance of Spam Filtering Methods When Dimensionality of Input Vector Changes

Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining

Probabilistic Model for Structured Document Mapping

Categorizing Evolved CoreWar Warriors Using EM and Attribute Evaluation

Distributed and Shared Memory Algorithm for Parallel Mining of Association Rules

Evolving Committees of Support Vector Machines

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science
Latest Publications