TY - GEN
T1 - Discovery of classifications from data of multiple sources
AU - Wen, Jun Hao
AU - Ling, Charles
AU - Yang, Qiang
PY - 2003
Y1 - 2003
N2 - We study a learning paradigm that bridges between supervised learning and unsupervised learning. In this paradigm, the learner is given unlabeled examples described by several sets of attributes. The task of learning is to (re) construct class labels consistent with the multiple sets of attributes. We design a novel learning algorithm, called AutoLabel, for this type of learning tasks, and we identify the source of power in the algorithm. We test AutoLabel on artificial and real-world datasets, and show that it constructs classification labels accurately. Our learning algorithm removes the fundamental assumption of providing class labels in supervised learning, and gives a new perspective to unsupervised learning.
AB - We study a learning paradigm that bridges between supervised learning and unsupervised learning. In this paradigm, the learner is given unlabeled examples described by several sets of attributes. The task of learning is to (re) construct class labels consistent with the multiple sets of attributes. We design a novel learning algorithm, called AutoLabel, for this type of learning tasks, and we identify the source of power in the algorithm. We test AutoLabel on artificial and real-world datasets, and show that it constructs classification labels accurately. Our learning algorithm removes the fundamental assumption of providing class labels in supervised learning, and gives a new perspective to unsupervised learning.
KW - Learning from unlabeled data
KW - Supervised learning
KW - Unsupervised learning
UR - https://www.scopus.com/pages/publications/1542285293
U2 - 10.1109/ICMLC.2003.1259887
DO - 10.1109/ICMLC.2003.1259887
M3 - Conference Paper published in a book
AN - SCOPUS:1542285293
SN - 0780378652
T3 - International Conference on Machine Learning and Cybernetics
SP - 2281
EP - 2286
BT - International Conference on Machine Learning and Cybernetics
T2 - 2003 International Conference on Machine Learning and Cybernetics
Y2 - 2 November 2003 through 5 November 2003
ER -