Showing 5 of total 5 results (show query)
ben519
mltools:Machine Learning Tools
A collection of machine learning helper functions, particularly assisting in the Exploratory Data Analysis phase. Makes heavy use of the 'data.table' package for optimal speed and memory efficiency. Highlights include a versatile bin_data() function, sparsify() for converting a data.table to sparse matrix format with one-hot encoding, fast evaluation metrics, and empirical_cdf() for calculating empirical Multivariate Cumulative Distribution Functions.
Maintained by Ben Gorman. Last updated 4 years ago.
exploratory-data-analysismachine-learning
72 stars 9.67 score 1.2k scripts 13 dependents
zpneal
backbone:Extracts the Backbone from Graphs
An implementation of methods for extracting an unweighted unipartite graph (i.e. a backbone) from an unweighted unipartite graph, a weighted unipartite graph, the projection of an unweighted bipartite graph, or the projection of a weighted bipartite graph (Neal, 2022 <doi:10.1371/journal.pone.0269137>).
Maintained by Zachary Neal. Last updated 1 years ago.
41 stars 7.06 score 31 scripts 2 dependents
clarahapp
funData:An S4 Class for Functional Data
S4 classes for univariate and multivariate functional data with utility functions. See <doi:10.18637/jss.v093.i05> for a detailed description of the package functionalities and its interplay with the MFPCA package for multivariate functional principal component analysis <https://CRAN.R-project.org/package=MFPCA>.
Maintained by Clara Happ-Kurz. Last updated 1 years ago.
14 stars 6.15 score 111 scripts 6 dependents
cfwp
rags2ridges:Ridge Estimation of Precision Matrices from High-Dimensional Data
Proper L2-penalized maximum likelihood estimators for precision matrices and supporting functions to employ these estimators in a graphical modeling setting. For details, see Peeters, Bilgrau, & van Wieringen (2022) <doi:10.18637/jss.v102.i04> and associated publications.
Maintained by Carel F.W. Peeters. Last updated 1 years ago.
c-plus-plusgraphical-modelsmachine-learningnetworksciencestatisticsopenblascpp
8 stars 5.60 score 46 scripts
nk027
sanic:Solving Ax = b Nimbly in C++
Routines for solving large systems of linear equations and eigenproblems in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Dense and sparse problems are supported.
Maintained by Nikolas Kuschnig. Last updated 2 years ago.
bicgstabcholeskyconjugate-gradienteigenlinear-equationssolverscpp
9 stars 4.13 score 1 scripts 1 dependents