Distance matrix
A distance matrix is a square array whose entries represent pairwise distances or dissimilarities between objects, points, or vertices.
Build a Robo-Advisor with Python (From Scratch)
A distance matrix is a square array whose entries represent pairwise dissimilarities between objects.
- How it is used
- Prepares correlated assets for hierarchical clustering in hierarchical risk parity portfolio allocation.
- How deep it goes
- Derives two distance matrices and implements both calculations, then defers cluster formation to later steps.
- Examples
- Uses eight ETF-like tickers and Python calculations of correlations, distances, and pairwise vector norms.
- What you can do after
- Build it from scratch by converting return correlations into clustering-ready distance matrices in Python.
Read how Build a Robo-Advisor with Python (From Scratch) explains distance matrix →
Statistics Slam Dunk
A distance matrix is a tabular structure containing pairwise distances or dissimilarities between observations.
- How it is used
- Supports hierarchical clustering by quantifying similarity between observations.
- How deep it goes
- Works through Euclidean calculations, R output, and dendrogram construction.
- Examples
- Uses NBA draft pick numbers and average career win shares, including hand-calculated pairwise distances.
- What you can do after
- Apply it via R's dist() and hclust() functions to produce hierarchical clusters.
Modern C
A distance matrix is a matrix whose entry for a pair of points records the distance from the first point to the second.
- How it is used
- Supports shortest-path reasoning by storing distances between ordered pairs of points in a graph.
- How deep it goes
- Defines the representation and sentinel convention, then asks for shortest-path work without supplying an algorithm.
- Examples
- Uses graph G, ordered points i and j, nodes x and y, and SIZE_MAX for absent direct arcs.
- What you can do after
- Evaluate a graph representation and formulate a shortest-path search between two specified nodes.
Related concepts
- correlation matrixproduced by · A correlation matrix is a square matrix whose entries represent pairwise correlation coefficients among a set of variables.
- haversine formulaproduced by · The Haversine formula computes the great-circle distance between two points on a sphere from their latitudes and longitudes.
- objective functionused by · An objective function assigns values to candidate solutions, predictions, or parameter settings according to a criterion to be minimized or maximized.
- Euclidean distanceused by · Euclidean distance is the straight-line distance between two points in Euclidean space, calculated as the square root of the sum of squared differences between corresponding coordinates.
- dist() functionproduced by · The dist() function in base R computes pairwise distances between observations using a specified distance measure.
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