Abstract
In machine learning, classification is considered an instance of the supervised learning methods, i.e., inferring a function from labeled training data. The training data consist of a set of training examples, where each example is a pair consisting of an input object (typically a vector) x = <x1,x2,…,xd> and a desired output value (typically a class label) y ∊ {C1,C2,…,CK}. Given such a set of training data, the task of a classification algorithm is to analyze the training data and produce an inferred function, which can be used to classify new (so far unseen) examples by assigning a correct class label to each of them. An example would be assigning a given email into “spam” or “non-spam” classes.
Original language | English (US) |
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Title of host publication | Data Classification |
Subtitle of host publication | Algorithms and Applications |
Editors | Charu C Aggarwal |
Publisher | CRC Press |
Pages | 65-86 |
Number of pages | 22 |
ISBN (Electronic) | 9781466586758 |
ISBN (Print) | 9781466586741 |
DOIs | |
State | Published - Jan 1 2014 |
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)
- Computer Science(all)