Nathan Smith Picture

Nathan Smith

Senior Data Scientist at Neo4j

Nathan is a Senior Data Scientist at Neo4j. He uses data and algorithms to solve problems and demystifies machine learning to help people use the tools of data science to make the world a better place.

Latest Posts by Nathan Smith

Clustering Large Graphs With CLARANS

In a previous article, I discussed the benefits of using k-medoids to cluster graph data. In the k-medoids approach, you determine how many clusters you would like to partition the graph into. This number is called k. The algorithm identifies a set of k nodes in the graph called medoids. The other... read more

Clustering Graph Data With K-Medoids

K-medoids is an approach for discovering clusters in data. It is similar to the well-known k-means algorithm.Both approaches require the analyst to select the number of output clusters before running the algorithm. This number is called k. Both algorithms assign each dataset member to one of... read more

Approximate Maximum K-Cut with Neo4j Graph Data Science

Cluster related products and separate conflicting entities with the newest algorithm in the Graph Data Science Library: Approximate Maximum K-cutPhoto by Matt Artz on UnsplashThe 1.7 release of Neo4j’s Graph Data Science Library contains some amazing features, like machine learning... read more