Showing 13 of total 13 results (show query)
rcppcore
RcppEigen:'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library
R and 'Eigen' integration using 'Rcpp'. 'Eigen' is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear systems. Its performance on many algorithms is comparable with some of the best implementations based on 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header files from the 'Eigen' C++ template library. Thus users do not need to install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License (version 2); earlier version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.
Maintained by Dirk Eddelbuettel. Last updated 7 months ago.
algorithmc-plus-pluseigeneigen-libraryopenblascpp
114 stars 15.66 score 356 scripts 3.8k dependents
immunogenomics
harmony:Fast, Sensitive, and Accurate Integration of Single Cell Data
Implementation of the Harmony algorithm for single cell integration, described in Korsunsky et al <doi:10.1038/s41592-019-0619-0>. Package includes a standalone Harmony function and interfaces to external frameworks.
Maintained by Ilya Korsunsky. Last updated 5 months ago.
algorithmdata-integrationscrna-seqopenblascpp
554 stars 13.74 score 5.5k scripts 8 dependents
bioc
target:Predict Combined Function of Transcription Factors
Implement the BETA algorithm for infering direct target genes from DNA-binding and perturbation expression data Wang et al. (2013) <doi: 10.1038/nprot.2013.150>. Extend the algorithm to predict the combined function of two DNA-binding elements from comprable binding and expression data.
Maintained by Mahmoud Ahmed. Last updated 5 months ago.
softwarestatisticalmethodtranscriptionalgorithmchip-seqdna-bindinggene-regulationtranscription-factors
4 stars 7.79 score 1.3k scripts
vlarmet
cppRouting:Algorithms for Routing and Solving the Traffic Assignment Problem
Calculation of distances, shortest paths and isochrones on weighted graphs using several variants of Dijkstra algorithm. Proposed algorithms are unidirectional Dijkstra (Dijkstra, E. W. (1959) <doi:10.1007/BF01386390>), bidirectional Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005) <https://archive.siam.org/meetings/alenex05/papers/03agoldberg.pdf>), A* search (P. E. Hart, N. J. Nilsson et B. Raphael (1968) <doi:10.1109/TSSC.1968.300136>), new bidirectional A* (Pijls & Post (2009) <https://repub.eur.nl/pub/16100/ei2009-10.pdf>), Contraction hierarchies (R. Geisberger, P. Sanders, D. Schultes and D. Delling (2008) <doi:10.1007/978-3-540-68552-4_24>), PHAST (D. Delling, A.Goldberg, A. Nowatzyk, R. Werneck (2011) <doi:10.1016/j.jpdc.2012.02.007>). Algorithms for solving the traffic assignment problem are All-or-Nothing assignment, Method of Successive Averages, Frank-Wolfe algorithm (M. Fukushima (1984) <doi:10.1016/0191-2615(84)90029-8>), Conjugate and Bi-Conjugate Frank-Wolfe algorithms (M. Mitradjieva, P. O. Lindberg (2012) <doi:10.1287/trsc.1120.0409>), Algorithm-B (R. B. Dial (2006) <doi:10.1016/j.trb.2006.02.008>).
Maintained by Vincent Larmet. Last updated 16 days ago.
algorithmalgorithm-bbidirectional-a-star-algorithmc-plus-pluscontraction-hierarchiesdijkstra-algorithmdistancefrank-wolfeisochronesparallel-computingrcppshortest-pathstraffic-assignmentcpp
113 stars 7.72 score 39 scripts 4 dependents
matrix-profile-foundation
tsmp:Time Series with Matrix Profile
A toolkit implementing the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
Maintained by Francisco Bischoff. Last updated 3 years ago.
algorithmmatrix-profilemotif-searchtime-seriescpp
72 stars 7.29 score 179 scripts 1 dependents
hongooi73
SAR:Smart Adaptive Recommendations
'Smart Adaptive Recommendations' (SAR) is the name of a fast, scalable, adaptive algorithm for personalized recommendations based on user transactions and item descriptions. It produces easily explainable/interpretable recommendations and handles "cold item" and "semi-cold user" scenarios. This package provides two implementations of 'SAR': a standalone implementation, and an interface to a web service in Microsoft's 'Azure' cloud: <https://github.com/Microsoft/Product-Recommendations/blob/master/doc/sar.md>. The former allows fast and easy experimentation, and the latter provides robust scalability and extra features for production use.
Maintained by Hong Ooi. Last updated 4 years ago.
21 stars 5.32 score 20 scripts
paulnorthrop
itp:The Interpolate, Truncate, Project (ITP) Root-Finding Algorithm
Implements the Interpolate, Truncate, Project (ITP) root-finding algorithm developed by Oliveira and Takahashi (2021) <doi:10.1145/3423597>. The user provides the function, from the real numbers to the real numbers, and an interval with the property that the values of the function at its endpoints have different signs. If the function is continuous over this interval then the ITP method estimates the value at which the function is equal to zero. If the function is discontinuous then a point of discontinuity at which the function changes sign may be found. The function can be supplied using either an R function or an external pointer to a C++ function. Tuning parameters of the ITP algorithm can be set by the user. Default values are set based on arguments in Oliveira and Takahashi (2021).
Maintained by Paul J. Northrop. Last updated 10 months ago.
algorithmbracketingitpitp-methodroot-findingcpp
12 stars 5.08 score 8 scripts
haghish
autoEnsemble:Automated Stacked Ensemble Classifier for Severe Class Imbalance
A stacking solution for modeling imbalanced and severely skewed data. It automates the process of building homogeneous or heterogeneous stacked ensemble models by selecting "best" models according to different criteria. In doing so, it strategically searches for and selects diverse, high-performing base-learners to construct ensemble models optimized for skewed data. This package is particularly useful for addressing class imbalance in datasets, ensuring robust and effective model outcomes through advanced ensemble strategies which aim to stabilize the model, reduce its overfitting, and further improve its generalizability.
Maintained by E. F. Haghish. Last updated 9 days ago.
aialgorithmautomated-machine-learningautomlautoml-algorithmsensembleensemble-learningh2oh2oaimachine-learningmachinelearningmetalearningstack-ensemblestacked-ensemblesstacking
5 stars 4.42 score 21 scripts
joshuawlambert
rFSA:Feasible Solution Algorithm for Finding Best Subsets and Interactions
Assists in statistical model building to find optimal and semi-optimal higher order interactions and best subsets. Uses the lm(), glm(), and other R functions to fit models generated from a feasible solution algorithm. Discussed in Subset Selection in Regression, A Miller (2002). Applied and explained for least median of squares in Hawkins (1993) <doi:10.1016/0167-9473(93)90246-P>. The feasible solution algorithm comes up with model forms of a specific type that can have fixed variables, higher order interactions and their lower order terms.
Maintained by Joshua Lambert. Last updated 4 years ago.
algorithmfsainteractionmodelsparallelstatisticalstatisticssubset
7 stars 4.15 score 20 scripts
petermeissner
crossword.r:Generating Crosswords from Word Lists
Generate crosswords from a list of words.
Maintained by Peter Meissner. Last updated 6 years ago.
28 stars 4.15 score 8 scripts
jwood000
RcppBigIntAlgos:Factor Big Integers with the Parallel Quadratic Sieve
Features the multiple polynomial quadratic sieve (MPQS) algorithm for factoring large integers and a vectorized factoring function that returns the complete factorization of an integer. The MPQS is based off of the seminal work of Carl Pomerance (1984) <doi:10.1007/3-540-39757-4_17> along with the modification of multiple polynomials introduced by Peter Montgomery and J. Davis as outlined by Robert D. Silverman (1987) <doi:10.1090/S0025-5718-1987-0866119-8>. Utilizes the C library GMP (GNU Multiple Precision Arithmetic). For smaller integers, a simple Elliptic Curve algorithm is attempted followed by a constrained version of Pollard's rho algorithm. The Pollard's rho algorithm is the same algorithm used by the factorize function in the 'gmp' package.
Maintained by Joseph Wood. Last updated 10 months ago.
algorithmgmpinteger-factorizationmpqsprime-factorizationsprimesquadratic-sievequadratic-sieve-algorithmcpp
13 stars 3.81 score 8 scriptsmatrix-profile-foundation
matrixprofiler:Matrix Profile for R
This is the core functions needed by the 'tsmp' package. The low level and carefully checked mathematical functions are here. These are implementations of the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
Maintained by Francisco Bischoff. Last updated 3 years ago.
algorithmmatrix-profilercpptime-seriescpp
10 stars 3.70 score 2 scripts
