A Narrative Study on Supervised Learning

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Volume 3, Issue 1 (January, 2017)
Publication No:
Paru Sharma, Dr. Raman Chadha
16 x

Supervised learning is the machine learning task of inferring a function from training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object and a desired output value. A supervised learning algorithm analyzes the training data and produces an output, which can be used for mapping new inputs. In supervised learning two types of variables are used in the algorithm namely, input variable (x) and output variable (y) and there is a mapping function from input to the output Y=f(x). It is called supervised leaning because it requires a teacher supervising the learning process. The algorithm makes the predictions on the training set in an iterative manner which is corrected by a teacher.