A confusion matrix for comparing gold clusters to some predicted clusters.
A trait for distance functions, which take two Points as arguments and return a Double representing the distance between them.
A point transformer that simply returns the points given to it.
A class for computing clusters for a set of points using k-means (specifically, Lloyd's algorithm).
A transformer that scales a set of points, maps them into a PCA space, and then reduces the dimensionality by retaining only the top components.
A simple representation of a point in some n-dimensional space.
A trait for functions that transform a set of points from one space to another space that is potentially scaled, reduced, or both.
A class for objects that transform Points to and from z-score values based on means and standard deviations in each dimension.
A companion object for constructing ClusterConfusionMatrices.
Compute the cosine distance between two points.
A companion object to the DistanceFunction trait that helps select the DistanceFunction corresponding to each string description.
Compute the Euclidean distance between two points.
Compute the Manhattan (city-block) distance between two points.
Companion object that constructs a ZscoreTransformer from the given points, and then computes the principal components from the scaled points.
A companion object to the PointTransformer trait to retrieve the point transformation functions corresponding to the given description.
Companion object that computes means and standard deviations to construct a ZscoreTransformer.