21. "Self-training " is a wrapper method for semi-supervised learning . 22. In supervised learning models, there are tests that are needed to pass to reduce mistakes. 23. The software implements any number of layers of non-linear processing units for supervised learning . 24. Hence, a supervised learning algorithm can be constructed by applying an optimization algorithm to find g. 25. Support vector machines ( SVMs ) are a set of related supervised learning methods used for regression. 26. Description : The first application of supervised learning to gene expression data, in particular Support Vector Machines. 27. And some researchers recently proposed Graph-based semi-supervised learning model for language specific NER tasks. 28. When labels are more expensive to gather than input examples, semi-supervised learning can be useful. 29. In empirical risk minimization, the supervised learning algorithm seeks the function g that minimizes R ( g ). 30. Semi-supervised learning is also of theoretical interest in machine learning and as a model for human learning.
