Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Co-training for predicting emotions with spoken dialogue data
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Word sense disambiguation using label propagation based semi-supervised learning
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Genetic-guided semi-supervised clustering algorithm with instance-level constraints
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Transductive multi-label learning for video concept detection
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Genetic programming for protein related text classification
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Introduction to Semi-Supervised Learning
Introduction to Semi-Supervised Learning
Modern Information Retrieval
Coevolutionary multi-population genetic programming for data classification
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Semi-Supervised Learning
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
Application of genetic programming for multicategory patternclassification
IEEE Transactions on Evolutionary Computation
A novel approach to design classifiers using genetic programming
IEEE Transactions on Evolutionary Computation
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
Learning from unlabeled data provides innumerable advantages to a wide range of applications where there is a huge amount of unlabeled data freely available. Semi-supervised learning, which builds models from a small set of labeled examples and a potential large set of unlabeled examples, is a paradigm that may effectively use those unlabeled data. Here we propose KGP, a semi-supervised transductive genetic programming algorithm for classification. Apart from being one of the first semi-supervised algorithms, it is transductive (instead of inductive), i.e., it requires only a training dataset with labeled and unlabeled examples, which should represent the complete data domain. The algorithm relies on the three main assumptions on which semi-supervised algorithms are built, and performs both global search on labeled instances and local search on unlabeled instances. Periodically, unlabeled examples are moved to the labeled set after a weighted voting process performed by a committee. Results on eight UCI datasets were compared with Self-Training and KNN, and showed KGP as a promising method for semi-supervised learning.