Abstract
In the construction of phylogenetic tree, the choice of a metric for measuring the distance of pairs of objects, and linkages for measuring distance between groups are both crucial. For stepwise methods, different linkages usually produce different trees, and for exhaustive methods, the computation is time-consuming when the number of objects to be classified is large. In this paper, we propose an ultrametric fuzzy distance, and show that under this distance, the correspondent distance tree is additive and linkage-free, and therefore has a one-to-one correspondence between the distance matrix and trees. The algorithm is easy to implement even for a large sample of objects; however, it may mildly increase the chance of misclassification due to the loss of information.
| Original language | English |
|---|---|
| Pages (from-to) | 443-449 |
| Number of pages | 7 |
| Journal | Fuzzy Sets and Systems |
| Volume | 122 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2001 Sep 16 |
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All Science Journal Classification (ASJC) codes
- Logic
- Artificial Intelligence
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Reconstruction of additive phylogenetic tree. / Lian, Ie Bin.
In: Fuzzy Sets and Systems, Vol. 122, No. 3, 16.09.2001, p. 443-449.Research output: Contribution to journal › Article
TY - JOUR
T1 - Reconstruction of additive phylogenetic tree
AU - Lian, Ie Bin
PY - 2001/9/16
Y1 - 2001/9/16
N2 - In the construction of phylogenetic tree, the choice of a metric for measuring the distance of pairs of objects, and linkages for measuring distance between groups are both crucial. For stepwise methods, different linkages usually produce different trees, and for exhaustive methods, the computation is time-consuming when the number of objects to be classified is large. In this paper, we propose an ultrametric fuzzy distance, and show that under this distance, the correspondent distance tree is additive and linkage-free, and therefore has a one-to-one correspondence between the distance matrix and trees. The algorithm is easy to implement even for a large sample of objects; however, it may mildly increase the chance of misclassification due to the loss of information.
AB - In the construction of phylogenetic tree, the choice of a metric for measuring the distance of pairs of objects, and linkages for measuring distance between groups are both crucial. For stepwise methods, different linkages usually produce different trees, and for exhaustive methods, the computation is time-consuming when the number of objects to be classified is large. In this paper, we propose an ultrametric fuzzy distance, and show that under this distance, the correspondent distance tree is additive and linkage-free, and therefore has a one-to-one correspondence between the distance matrix and trees. The algorithm is easy to implement even for a large sample of objects; however, it may mildly increase the chance of misclassification due to the loss of information.
UR - http://www.scopus.com/inward/record.url?scp=0035899784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035899784&partnerID=8YFLogxK
U2 - 10.1016/S0165-0114(00)00053-1
DO - 10.1016/S0165-0114(00)00053-1
M3 - Article
AN - SCOPUS:0035899784
VL - 122
SP - 443
EP - 449
JO - Fuzzy Sets and Systems
JF - Fuzzy Sets and Systems
SN - 0165-0114
IS - 3
ER -