#Definition: What is supervised learning in AI?

The media update team explores the topic.

Supervised learning can be defined as a type of machine learning algorithm that relies on a training dataset to make predictions.

Breaking it down to basics, supervised machine learning is when a system receives a training dataset made up of input data and corresponding output data. From the training data, the system learns how the input led to the output data, creating a model – or what is called a ‘mapping function’.

It can then be given different input data to predict what the output would be, based on the patterns it recognised in the training set it has learnt from.

A simple example of how this process works is a system that learns from a database of fruit and their corresponding characteristics. The system would, for instance, learn that the attributes “yellow”, “soft flesh”, “tropical plant” and “potassium” equals “banana”.

It could then be applied to a database that only lists the characteristics of fruit. The model it has created during the supervised machine learning process will be able to predict the type of fruit by considering the attributes in the dataset.

Supervised learning is also being employed for sophisticated tasks like detecting fraud in credit card transactions. In this use case, the system is given a database of past fraud incidents and the attributes of each of these cases. With the model it creates, it can then be used to consider the characteristics of current credit card transactions and predict which ones are fraudulent.

Supervised machine learning can also be used to determine specific values, such as the amount of weight, amount of sales or price. Learning from a database of characteristics that identify houses and their corresponding prices, a system could, for instance, predict the prices of other houses.  

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This form of artificial intelligence has the ability to affect a number of industries. Find out which sectors will feel the impact of AI this year in our article, Three industries AI will change in 2018.