We are already aware of supervised and unsupervised machine learning algorithm as discussed in our previous sections. Let us understand K means clustering first. It is an unsupervised machine learning algorithm used for clustering where the algorithm is trained to divide the whole data set into different clusters as decided by the user. K is the number of predefined clusters.
The number of clusters that the algorithm is supposed to form is defined by the k-means clustering.
Whereas, KNN is K Nearest Neighbour algorithm, it is a supervised learning technique used for regression or classification. The algorithm is trained to identify any random unit and after that, the algorithm tries to locate the nearest neighbours based on the association of characteristics.
The number ‘K’ represents the number of nearest neighbours that the particular algorithm is supposed to find.
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