Supervised learning is a type of machine learning in which data is fully labeled and algorithms learn to approximate a mapping function well enough that they can accurately predict output variables given new input data. This section contains supervised learning techniques. For example, Support Vector Machine (SVM), is a type of algorithm that is a discriminative classifier formally defined by a separating hyperplane used for regression and classification tasks.
Supervised learning is predicated on the use of well-labeled data. There are a number of companies in the data labeling software industry.
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