Improving imbalanced multidimensional dataset learner performance with artificial data generation: Density-based class-boost algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5077 LNAI, Issue , 2008, Pages 165-176

  Malazizi, Ladan ^a   Neagu, Daniel ^a   Chaudhry, Qasim ^a  

^a NONE

Author keywords

Class Boost; Density based Clustering; Imbalanced multidimensional dataset

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; CLASSIFICATION (OF INFORMATION); CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; DATA MINING; DATA STRUCTURES; DECISION SUPPORT SYSTEMS; ELECTRONIC COMMERCE; FILE ORGANIZATION; FLOW OF SOLIDS; HEALTH; IMAGE RESOLUTION; INFORMATION MANAGEMENT; LEARNING SYSTEMS; MATRIX ALGEBRA; MEDICAL APPLICATIONS; MINING; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; RISK ASSESSMENT; SEARCH ENGINES;

ARTIFICIAL DATA; CHALLENGING TASK; CLASS-BOOST; CLASSIFICATION ACCURACIES; CLASSIFICATION ALGORITHMS; CLASSIFIER PERFORMANCE; CONFUSION MATRICES; DATA MODELLING; DATA SETS; DENSITY-BASED; DENSITY-BASED CLUSTERING; E-COMMERCE; F-MEASURE; IMBALANCED DATASETS; IMBALANCED MULTIDIMENSIONAL DATASET; MACHINE-LEARNING; MULTI-DIMENSIONAL DATASETS; MULTI-DIMENSIONAL SPACES; NEW APPROACHES; PROBABILITY DENSITIES; TP RATE; TRAINING DATA; TRAINING SETS; TRUE POSITIVE RATE;

MEDICAL COMPUTING;

EID: 48949088239     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-70720-2_13     Document Type: Conference Paper

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