In this section and the ones that follow, we will be taking a closer look at several specific algorithms for supervised and unsupervised learning, starting here with naive Bayes classification. Naive Bayes models are a group of extremely fast and simple classification algorithms that are often suitable for very high-dimensional datasets. 3 Semi-supervised self-training with decision trees In this section, we ?rst de?ne the Semi-supervised setting and then address the semi-supervised self-training algorithm. 3.1 Semi-supervised setting In semi-supervised learning there is a small set of labeled data and a large pool of unlabeled data. Data points are divided into the points Semi-supervised learning is to applied to use both labelled and unlabelled data in order to produce better results than the normal approaches. Source: link. End Notes. I hope that now you have a understanding what semi-supervised learning is and how to implement it in any real world problem. Scalable Semi-Supervised Aggregation of Classi?ers Akshay Balsubramani UC San Diego abalsubr@cs.ucsd.edu Yoav Freund UC San Diego yfreund@cs.ucsd.edu Abstract We present and empirically evaluate an ef?cient algorithm that learns to aggre-gate the predictions of an ensemble of binary classi?ers. The algorithm uses the The general idea of semi-supervised methodis to train the classifier first with a small set of available labelled data and then iteratively retrain the classifier with the big set of unlabelled data. In this paper, we use a raw well-logging data from the. Jianghan oilfield to test the performance of a semi-supervised neural network classifier. (Supervised / Semi-Supervised) Request for the label of another data point Request for the label of a data point Activized Learning "Activizer" Meta-algorithm Expert / Oracle Data Source Algorithm outputs a classifier The label of that point The label of that point . . . Are there general-purpose activizers that strictly improve Face Recognition with semi-supervised learning and Multiple Classifiers NEAMAT EL GAYAR*, SHABAN A. SHABAN† SAYED HAMDY† †Institute of Statistical Studies and Research *Faculty of Computers and Information Cairo University 5 Ahmed Zewel St., 12613 Orman, Giza advances in time series query filtering to use these classifiers very efficiently, particularly for streaming problems [41]. To enhance the readers' appreciation of the diversity of domains which can benefit from a semi-supervised technique for building time series classifiers, we begin by considering some applications The Essential Supervisor's Handbook: A Quick and Handy Guide for Any Manager or Business Owner [Brette Mcwhorter Sember, Terrence J. Sember] on Amazon.com. *FREE* shipping on qualifying offers. The key to a good business is good employees. The key to good employees? A great supervisor. The Essential Supervisor's Handbook provides a guide for both new and experienced supervisors featuring CiteSeerX - Document Details (Isaac