Clustering

How it is used

Common algorithms are k-means, DBSCAN and hierarchical clustering. Each group is a cluster, and items are said to 'cluster together'. It is often run on embeddings to find themes in large collections of texts or images.

Example sentences

1. Clustering the complaints revealed three main themes: delivery, refunds and app crashes.

2. We ran clustering on the embeddings and then named each cluster by hand.

Common collocations

• k-means clustering
• run clustering
• cluster analysis
• customer clustering

Related terms

• unsupervised learningA type of machine learning that finds structure in data without correct answers (labels), for example grouping similar customers or spotting unusual events.
• embeddingA list of numbers (a vector) that represents a word, sentence, image or other item in such a way that items with similar meanings end up close to each other.
• featureA piece of functionality that users can see or use, such as a search bar, dark mode or the option to export a report.
• datasetA collection of examples, such as images, texts or table rows, gathered and organized for training, testing or analyzing a model.

This word in other fields

The same English word can have a different meaning in another field:

• clustering · Data Science & Analytics
• clustering · Artificial Intelligence & Machine Learning

More terms: Machine Learning and Data Processing

• artificial intelligence
• machine learning
• model
• training data
• label
• train
• supervised learning
• neural network
• deep learning
• loss function
• overfitting
• test set