Supervised Learning System

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A Supervised Learning System is a machine learning system that can learn to predict an output given an input dataset.




  • (Wikipedia, 2017) ⇒ Retrieved:2017-12-24.
    • Supervised learning is the machine learning task of inferring a function from. [1] The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).

      The parallel task in human and animal psychology is often referred to as concept learning.

  1. Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar (2012) Foundations of Machine Learning, The MIT Press .