K-mean clustering

▪ Before we learn about k-mean clustering let’s get some root knowledge

Today we generate a large amount of data, it can be related to population, jobs, production, defects in the production as well.

The most basic example is researchers have clustered plant and animal kingdoms and further they are sub clustered according to most common features.

▪ but what is the need for clustering?

let us consider a large amount of data from all over India, and now you need to research about literacy rate. so for this one will get a huge amount of variation plus this technique may ignore outliers, rather than this he can make clusters of populations sharing similar geographical areas along with the regional development like rural and urban regions. the similarities within rural regions will be greater, wherein the difference between the rural and urban regions will be greater, this will solve the complexity of the problem and sorts the data points.

▪ Clustering analysis groups things based on the information found in the data describing those objects and their relationships.

Now, how to cluster the things depends on use cases, and plus one should be able to find the most optimized clustering for the problem.

One of the most frequently used clusterings is centroid based clustering i.e K-mean clustering, the algorithm aims at classifying objects to particular clusters,

here, priority is set to the center of the cluster, not its borders or spread.

▪ K-means clustering is a powerful unsupervised machine learning algorithm. It is used to solve many complex unsupervised machine learning problems.

Today, computer network security has become the chief problem of the information society. With the continuous development of technology, network intrusion behavior has increased, Therefore, network security is the most important component of today’s society.

As for the detection and prevention of intrusion detection, it becomes the primary problem that we need to solve. Based on the data mining of the k-means clustering algorithm. they determine the intruder behavior and further solve the holes which can lead to intrusion.

Hope you all find it interesting..!!!

Thankyou..!!!