TY - GEN
T1 - Decision-tree Induction from Time-series Data Based on a Standard-example Split Test
AU - Yamada, Yuu
AU - Suzuki, Einoshin
AU - Yokoi, Hideto
AU - Takabayashi, Katsuhiko
PY - 2003
Y1 - 2003
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=1942451954&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=1942451954&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:1942451954
SN - 1577351894
T3 - Proceedings, Twentieth International Conference on Machine Learning
SP - 840
EP - 847
BT - Proceedings, Twentieth International Conference on Machine Learning
A2 - Fawcett, T.
A2 - Mishra, N.
T2 - Proceedings, Twentieth International Conference on Machine Learning
Y2 - 21 August 2003 through 24 August 2003
ER -