O'Reilly logo

Apache Mahout Essentials by Jayani Withanawasam

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Additional clustering algorithms

The K-Means algorithm is a simple and fast algorithm for clustering. However, this algorithm has its own limitations in certain scenarios. So, we will explain other clustering algorithms that are available in Apache Mahout here.

Canopy clustering

The accuracy of the K-Means algorithm depends on the number of clusters (K) and the initial cluster points that we randomly generated.

K-Means used org.apache.mahout.clustering.kmeans.RandomSeedGenerator to determine initial clusters randomly. However, with this approach, there is no guarantee about the time to converge, so it might take a long time for a large dataset to converge. Sometimes, premature convergence may occur due to the inability to pass a local optimum.

As ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required