Different supervised as well as unsupervised multivariate statistical methods are widely and successfully used in archaeometric data analysis.
Neural networks constitute a standard tool for diverse machine learning tasks in the supervised as well as the unsupervised domain, addressing issues such as function approximation, classification, dynamic system modeling, associative memory, etc.
Even unsupervised learning is semi-supervised, as it requires data scientists to choose the training data that goes into the models.
First, our approach could not always defeat supervised learners as it is seen from Tables 3 and 5.
It includes independent supervised activities, as well as educational, cultural and sports activities (Ministère de la Communauté française 2003).
This type of approach is known as semi-supervised learning (Zhu, 2005), as it combines ideas from supervised learning (classification) and unsupervised learning (clustering).
"The use of more paralegals at the police station is not inevitably a threat to quality provided that they are trained and supervised, and as long as work is suitably allocated.
We refer to this classifier as semi-supervised because it is learned using both labeled and unlabeled data.
Among the methods used here, SRG using region averaging is considered as supervised segmentation since it requires user involvement, and the rest are considered as unsupervised automatic segmentation.
A Lancet editorial cautioned that not all local health workers are as well trained and supervised as Pakistan's and that since northern Pakistan has a low AIDS rate, it would be wrong to assume that every country would do as well with such a system.
Irish banks were not as well supervised as they should have been.
