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ICML
2003
IEEE

Decision-tree Induction from Time-series Data Based on a Standard-example Split Test

14 years 4 months ago
Decision-tree Induction from Time-series Data Based on a Standard-example Split Test
This paper proposes a novel decision tree for a data set with time-series attributes. Our time-series tree has a value (i.e. a time sequence) of a time-series attribute in its internal node, and splits examples based on dissimilarity between a pair of time sequences. Our method selects, for a split test, a time sequence which exists in data by exhaustive search based on class and shape information. Experimental results confirm that our induction method constructs comprehensive and accurate decision trees. Moreover, a medical application shows that our time-series tree is promising for knowledge discovery.
Yuu Yamada, Einoshin Suzuki, Hideto Yokoi, Katsuhi
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2003
Where ICML
Authors Yuu Yamada, Einoshin Suzuki, Hideto Yokoi, Katsuhiko Takabayashi
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