On multi‐class cost‐sensitive learning
Rescaling is possibly the most popular approach to cost‐sensitive learning. This approach
works by rebalancing the classes according to their costs, and it can be realized in different …
works by rebalancing the classes according to their costs, and it can be realized in different …
[PDF][PDF] On Multi-Class Cost-Sensitive Learning
ZH Zhou, XY Liu - 2006 - fileadmin.cs.lth.se
A popular approach to cost-sensitive learning is to rescale the classes according to their
misclassification costs. Although this approach is effective in dealing with binary-class …
misclassification costs. Although this approach is effective in dealing with binary-class …
On multi-class cost-sensitive learning
ZH Zhou, XY Liu - Proceedings of the 21st national conference on …, 2006 - dl.acm.org
A popular approach to cost-sensitive learning is to rescale the classes according to their
misclassification costs. Although this approach is effective in dealing with binary-class …
misclassification costs. Although this approach is effective in dealing with binary-class …
[PDF][PDF] On Multi-Class Cost-Sensitive Learning
ZH Zhou, XY Liu - 2006 - 129.211.169.156
A popular approach to cost-sensitive learning is to rescale the classes according to their
misclassification costs. Although this approach is effective in dealing with binary-class …
misclassification costs. Although this approach is effective in dealing with binary-class …
ON MULTI-CLASS COST-SENSITIVE LEARNING.
ZHIHUA ZHOU, XUY LIU - Computational Intelligence, 2010 - search.ebscohost.com
Rescaling is possibly the most popular approach to cost-sensitive learning. This approach
works by rebalancing the classes according to their costs, and it can be realized in different …
works by rebalancing the classes according to their costs, and it can be realized in different …
[PDF][PDF] On Multi-Class Cost-Sensitive Learning
ZH Zhou, XY Liu - 2006 - lamda.nju.edu.cn
A popular approach to cost-sensitive learning is to rescale the classes according to their
misclassification costs. Although this approach is effective in dealing with binary-class …
misclassification costs. Although this approach is effective in dealing with binary-class …
On multi-class cost-sensitive learning.
ZH Zhou, XY Liu - Computational Intelligence, 2010 - psycnet.apa.org
Rescaling is possibly the most popular approach to cost-sensitive learning. This approach
works by rebalancing the classes according to their costs, and it can be realized in different …
works by rebalancing the classes according to their costs, and it can be realized in different …
ON MULTI‐CLASS COST‐SENSITIVE LEARNING
ZH Zhou, XY Liu - Computational Intelligence, 2010 - infona.pl
Rescaling is possibly the most popular approach to cost‐sensitive learning. This approach
works by rebalancing the classes according to their costs, and it can be realized in different …
works by rebalancing the classes according to their costs, and it can be realized in different …
[PDF][PDF] On Multi-Class Cost-Sensitive Learning
ZH Zhou, XY Liu - 2006 - cdn.aaai.org
A popular approach to cost-sensitive learning is to rescale the classes according to their
misclassification costs. Although this approach is effective in dealing with binary-class …
misclassification costs. Although this approach is effective in dealing with binary-class …
ON MULTI‐CLASS COST‐SENSITIVE LEARNING
ZH Zhou, XY Liu - Computational Intelligence, 2010 - cir.nii.ac.jp
抄録< jats: p>< jats: italic> Rescaling</jats: italic> is possibly the most popular approach to
cost‐sensitive learning. This approach works by rebalancing the classes according to their …
cost‐sensitive learning. This approach works by rebalancing the classes according to their …