Data Clustering Concepts

These flashcards cover key vocabulary and concepts related to data clustering, providing definitions and explanations of important terms.

Clustering

The process of organizing objects into groups whose members are similar in some way.

Cluster Analysis

A statistical method used to classify objects into distinct subgroups based on similarity.

Data Clustering

An unsupervised learning problem where the goal is to group examples into K partitions based on similarity.

High within-cluster similarity

Indicates that objects in the same cluster are very similar to each other.

Low inter-cluster similarity

Indicates that objects in different clusters are very dissimilar to each other.

Similarity

The quality or state of being similar; likeness; resemblance.

Distance Metrics

Functions that define a measure of distance between two data points, such as Euclidean or Manhattan distance.

Hierarchical Clustering

A clustering method that creates a hierarchy of clusters using either agglomerative or divisive approaches.

Agglomerative Clustering

A bottom-up approach to clustering where each data point starts as a single cluster.

K-means Clustering

A method that partitions data into K distinct clusters based on means of the data points in each cluster.

Gaussian Mixture Models (GMM)

A probabilistic model that assumes all data points are generated from a mixture of K Gaussian distributions.

Spectral Clustering

A clustering technique that uses the eigen-decomposition of similarity matrices to group data.

DBSCAN

A density-based clustering algorithm that defines clusters as regions of high point density.

Silhouette Score

A metric that quantifies how well each point lies within its cluster versus the next closest cluster.

Within-Cluster Sum of Squares (WCSS)

A measure of the total variance within clusters, often used to evaluate the quality of clustering.

Chebyshev Distance

A distance metric defined as the maximum absolute difference in any dimension between two points.

Cosine Similarity

A similarity measure that calculates the cosine of the angle between two non-zero vectors, often used in high-dimensional spaces.