bipartite_learn.preprocessing.monopartite

Functions

enforce_positive_semidefiniteness(X[, tol])	Enforce positive-semidefiniteness of kernel matrix.
nearest_positive_semidefinite(X)	Get nearest (Frobenius norm) positive semidefinite matrix from A.

Classes

PositiveSemidefiniteEnforcer([tol])	Modify main diagonal to enforce positive semidefiniteness.
SimilarityDistanceSwitcher()	Transforms x into (1 - x).
SymmetryEnforcer([sampling_strategy])	Make matrix symmetric by averaging it with its transpose.
TargetKernelDiffuser([n_iter, n_neighbors, ...])	Calculates kernel on y and performs non-linear kernel diffusion.
TargetKernelLinearCombiner([alpha, metric, ...])	Combines provided similarity matrix X with kernel calculated over y