Posted On: Apr 01, 2020
Supervised and unsupervised are the two types of Machine learning algorithms available.
In the supervised type, the algorithms are applied to the known labeled data to formulate a model. Labeled data means the data is tagged. With this data, the algorithm creates a model that is then applied to unknown data to predict its outcome or tag it. Linear regression is a good example of supervised learning.
In the unsupervised type, the algorithm is applied to the unlabeled data. The data neither is classified nor labeled, but the unsupervised algorithm is used to find the hidden structure with the unlabeled data. K-means clustering algorithm is a good example of this type.
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Regression is the process of estimating the mapping function (f) given the input value (x) to the continuous output value (y). It is used to predict a value given the data. Here, labeled data is used ...