TY - GEN
T1 - Fast induction of multiple decision trees in text categorization from large scale, imbalanced, and multi-label data
AU - Vateekul, Peerapon
AU - Kubat, Miroslav
PY - 2009/12/1
Y1 - 2009/12/1
N2 - The paper focuses on automated categorization of text documents, each labeled with one or more classes and described by tens of thousands of features. The computational costs of induction in such domains are so high as almost to disqualify the use of decision trees; the reduction of these costs is thus an important research issue. Our own solution, FDT ("fast decision-tree induction"), uses a two-pronged strategy: (1) feature-set pre-selection, and (2) induction of several trees, each from a different data subset, with the combination of the results from multiple trees with a data-fusion technique tailored to domains with imbalanced classes.
AB - The paper focuses on automated categorization of text documents, each labeled with one or more classes and described by tens of thousands of features. The computational costs of induction in such domains are so high as almost to disqualify the use of decision trees; the reduction of these costs is thus an important research issue. Our own solution, FDT ("fast decision-tree induction"), uses a two-pronged strategy: (1) feature-set pre-selection, and (2) induction of several trees, each from a different data subset, with the combination of the results from multiple trees with a data-fusion technique tailored to domains with imbalanced classes.
KW - Decision tree
KW - Imbalanced classes
KW - Large-scale data
KW - Multi-label examples
KW - Text categorization
UR - http://www.scopus.com/inward/record.url?scp=77951150128&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951150128&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2009.94
DO - 10.1109/ICDMW.2009.94
M3 - Conference contribution
AN - SCOPUS:77951150128
SN - 9780769539027
T3 - ICDM Workshops 2009 - IEEE International Conference on Data Mining
SP - 320
EP - 325
BT - ICDM Workshops 2009 - IEEE International Conference on Data Mining
T2 - 2009 IEEE International Conference on Data Mining Workshops, ICDMW 2009
Y2 - 6 December 2009 through 6 December 2009
ER -