Classification

• Published in: Introduction To Pattern Recognition And Machine Learning Vol. 5; p. 1
• Main Authors: Murty M Narasimha, Devi V Susheela
• Format: Book Chapter
• Language: English
• Published: Singapore World Scientific 2015; World Scientific Publishing Company; Co-Published with Indian Institute of Science (IISc), Bangalore, India
• Series: IISc Lecture Notes Series
• Subjects: Computer Hardware Engineering; Embedded Systems & Programming; General References; Pattern recognition; Software Engineering
• ISBN: 9814335452; 9789814335454; 9814656275; 9789814335461; 9814335460; 9789814656276
• DOI: 10.1142/9789814335461_0005

Classification is the task of assigning a class label to an input pattern. The class label indicates one of a given set of classes. The classification is carried out with the help of a model obtained using a learning procedure. According to the type of learning used, there are two categories of classification, one using supervised learning and the other using unsupervised learning. Supervised learning makes use of a set of examples which already have the class labels assigned to them. Unsupervised learning attempts to find inherent structures in the data. Semi-supervised learning makes use of a small number of labeled data and a large number of unlabeled data to learn the classifier.