Introduction to K-
Means Clustering
K-Means Clustering is a popular unsupervised machine learning algorithm
used to group similar data points into distinct clusters.
Here K defines the number of pre-defined clusters that need to be created in
the process, as if K=2, there will be two clusters, and for K=3, there will be
three clusters, and so on.
, Definition of K-Means Clustering
K-Means Clustering is a fundamental unsupervised machine learning algorithm used to group simil
data points into distinct clusters. The algorithm aims to partition the data into K clusters, where ea
observation belongs to the cluster with the nearest mean, serving as a representative prototype of
cluster.
Means Clustering
K-Means Clustering is a popular unsupervised machine learning algorithm
used to group similar data points into distinct clusters.
Here K defines the number of pre-defined clusters that need to be created in
the process, as if K=2, there will be two clusters, and for K=3, there will be
three clusters, and so on.
, Definition of K-Means Clustering
K-Means Clustering is a fundamental unsupervised machine learning algorithm used to group simil
data points into distinct clusters. The algorithm aims to partition the data into K clusters, where ea
observation belongs to the cluster with the nearest mean, serving as a representative prototype of
cluster.
