Showing 47 of total 47 results (show query)
jlmelville
rnndescent:Nearest Neighbor Descent Method for Approximate Nearest Neighbors
The Nearest Neighbor Descent method for finding approximate nearest neighbors by Dong and co-workers (2010) <doi:10.1145/1963405.1963487>. Based on the 'Python' package 'PyNNDescent' <https://github.com/lmcinnes/pynndescent>.
Maintained by James Melville. Last updated 8 months ago.
approximate-nearest-neighbor-searchcpp
107.2 match 11 stars 7.31 score 75 scriptsjlmelville
RcppHNSW:'Rcpp' Bindings for 'hnswlib', a Library for Approximate Nearest Neighbors
'Hnswlib' is a C++ library for Approximate Nearest Neighbors. This package provides a minimal R interface by relying on the 'Rcpp' package. See <https://github.com/nmslib/hnswlib> for more on 'hnswlib'. 'hnswlib' is released under Version 2.0 of the Apache License.
Maintained by James Melville. Last updated 3 months ago.
approximate-nearest-neighbor-searchhnswk-nearest-neighborsknnnearest-neighbor-searchnmslibrcppcpp
60.2 match 36 stars 10.07 score 63 scripts 77 dependents
eddelbuettel
RcppAnnoy:'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest Neighbors
'Annoy' is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from / save to disk. This package provides an R interface by relying on the 'Rcpp' package, exposing the same interface as the original Python wrapper to 'Annoy'. See <https://github.com/spotify/annoy> for more on 'Annoy'. 'Annoy' is released under Version 2.0 of the Apache License. Also included is a small Windows port of 'mmap' which is released under the MIT license.
Maintained by Dirk Eddelbuettel. Last updated 8 days ago.
annoynearestnearest-neighborscpp
39.9 match 72 stars 11.97 score 57 scripts 147 dependents
satijalab
Seurat:Tools for Single Cell Genomics
A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Maintained by Paul Hoffman. Last updated 1 years ago.
human-cell-atlassingle-cell-genomicssingle-cell-rna-seqcpp
26.6 match 2.4k stars 16.86 score 50k scripts 73 dependents
bioc
BiocNeighbors:Nearest Neighbor Detection for Bioconductor Packages
Implements exact and approximate methods for nearest neighbor detection, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Exact searches can be performed using the k-means for k-nearest neighbors algorithm or with vantage point trees. Approximate searches can be performed using the Annoy or HNSW libraries. Searching on either Euclidean or Manhattan distances is supported. Parallelization is achieved for all methods by using BiocParallel. Functions are also provided to search for all neighbors within a given distance.
Maintained by Aaron Lun. Last updated 12 days ago.
43.7 match 10.14 score 646 scripts 89 dependents
mhahsler
dbscan:Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms
A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.
Maintained by Michael Hahsler. Last updated 2 months ago.
clusteringdbscandensity-based-clusteringhdbscanlofopticscpp
27.1 match 321 stars 15.62 score 1.6k scripts 84 dependents
paulnorthrop
donut:Nearest Neighbour Search with Variables on a Torus
Finds the k nearest neighbours in a dataset of specified points, adding the option to wrap certain variables on a torus. The user chooses the algorithm to use to find the nearest neighbours. Two such algorithms, provided by the packages 'RANN' <https://cran.r-project.org/package=RANN>, and 'nabor' <https://cran.r-project.org/package=nabor>, are suggested.
Maintained by Paul J. Northrop. Last updated 2 years ago.
degreesdonutedgesknn-algorithmknn-searchnabornearestnearest-neighbornearest-neighbor-searchnearest-neighborsnearest-neighbour-algorithmnearest-neighboursneighborsperiodicityranntoruswrap
87.0 match 1 stars 4.18 score 5 scripts 1 dependents
jefferislab
RANN:Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric
Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' for the same functionality using the L1 (Manhattan, taxicab) metric.
Maintained by Gregory Jefferis. Last updated 7 months ago.
ann-librarynearest-neighborsnearest-neighbourscpp
29.4 match 58 stars 12.21 score 1.3k scripts 190 dependents
klausvigo
kknn:Weighted k-Nearest Neighbors
Weighted k-Nearest Neighbors for Classification, Regression and Clustering.
Maintained by Klaus Schliep. Last updated 4 years ago.
29.5 match 23 stars 11.08 score 4.6k scripts 41 dependentssatijalab
SeuratObject:Data Structures for Single Cell Data
Defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. Provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
Maintained by Paul Hoffman. Last updated 1 years ago.
24.9 match 25 stars 11.69 score 1.2k scripts 88 dependents
mlampros
KernelKnn:Kernel k Nearest Neighbors
Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations.
Maintained by Lampros Mouselimis. Last updated 2 years ago.
cpp11distance-metrickernel-methodsknnrcpparmadilloopenblascppopenmp
24.9 match 17 stars 9.16 score 54 scripts 13 dependents
jefferis
nabor:Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low Dimensions
An R wrapper for 'libnabo', an exact or approximate k nearest neighbour library which is optimised for low dimensional spaces (e.g. 3D). 'libnabo' has speed and space advantages over the 'ANN' library wrapped by package 'RANN'. 'nabor' includes a knn function that is designed as a drop-in replacement for 'RANN' function nn2. In addition, objects which include the k-d tree search structure can be returned to speed up repeated queries of the same set of target points.
Maintained by Gregory Jefferis. Last updated 5 years ago.
21.7 match 22 stars 8.21 score 104 scripts 34 dependents
kisungyou
Rdimtools:Dimension Reduction and Estimation Methods
We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You and Shung (2022) <doi:10.1016/j.simpa.2022.100414>.
Maintained by Kisung You. Last updated 2 years ago.
dimension-estimationdimension-reductionmanifold-learningsubspace-learningopenblascppopenmp
13.2 match 52 stars 8.37 score 186 scripts 8 dependentsmlampros
nmslibR:Non Metric Space (Approximate) Library
A Non-Metric Space Library ('NMSLIB' <https://github.com/nmslib/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/nmslib/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/nmslib/nmslib> 'Python' Library.
Maintained by Lampros Mouselimis. Last updated 2 years ago.
approximate-nearest-neighbor-searchnmslibnon-metricpythonreticulatecppopenmp
20.2 match 12 stars 5.14 score 23 scriptsbioc
tidytof:Analyze High-dimensional Cytometry Data Using Tidy Data Principles
This package implements an interactive, scientific analysis pipeline for high-dimensional cytometry data built using tidy data principles. It is specifically designed to play well with both the tidyverse and Bioconductor software ecosystems, with functionality for reading/writing data files, data cleaning, preprocessing, clustering, visualization, modeling, and other quality-of-life functions. tidytof implements a "grammar" of high-dimensional cytometry data analysis.
Maintained by Timothy Keyes. Last updated 5 months ago.
singlecellflowcytometrybioinformaticscytometrydata-sciencesingle-celltidyversecpp
13.4 match 19 stars 7.26 score 35 scripts
mlr-org
mlr3learners:Recommended Learners for 'mlr3'
Recommended Learners for 'mlr3'. Extends 'mlr3' with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.
Maintained by Marc Becker. Last updated 4 months ago.
classificationlearnersmachine-learningmlr3regression
8.2 match 91 stars 11.51 score 1.5k scripts 10 dependents
biooss
sensitivity:Global Sensitivity Analysis of Model Outputs and Importance Measures
A collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.
Maintained by Bertrand Iooss. Last updated 7 months ago.
11.7 match 17 stars 6.74 score 472 scripts 8 dependents
nsaph-software
GPCERF:Gaussian Processes for Estimating Causal Exposure Response Curves
Provides a non-parametric Bayesian framework based on Gaussian process priors for estimating causal effects of a continuous exposure and detecting change points in the causal exposure response curves using observational data. Ren, B., Wu, X., Braun, D., Pillai, N., & Dominici, F.(2021). "Bayesian modeling for exposure response curve via gaussian processes: Causal effects of exposure to air pollution on health outcomes." arXiv preprint <doi:10.48550/arXiv.2105.03454>.
Maintained by Boyu Ren. Last updated 11 months ago.
11.8 match 9 stars 6.33 score 16 scripts
fridleylab
spatialTIME:Spatial Analysis of Vectra Immunoflourescent Data
Visualization and analysis of Vectra Immunoflourescent data. Options for calculating both the univariate and bivariate Ripley's K are included. Calculations are performed using a permutation-based approach presented by Wilson et al. <doi:10.1101/2021.04.27.21256104>.
Maintained by Fridley Lab. Last updated 7 months ago.
12.2 match 4 stars 6.08 score 30 scripts
rcurtin
mlpack:'Rcpp' Integration for the 'mlpack' Library
A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. See also Curtin et al. (2023) <doi:10.21105/joss.05026>.
Maintained by Ryan Curtin. Last updated 3 months ago.
18.1 match 3.71 score 20 scripts 8 dependents
animint
animint2:Animated Interactive Grammar of Graphics
Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Maintained by Toby Hocking. Last updated 27 days ago.
6.9 match 64 stars 8.87 score 173 scripts
tkonopka
umap:Uniform Manifold Approximation and Projection
Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in <arXiv:1802.03426>. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).
Maintained by Tomasz Konopka. Last updated 11 months ago.
dimensionality-reductionumapcpp
4.5 match 132 stars 12.74 score 3.6k scripts 43 dependents
grasia
knnp:Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)
Two main functionalities are provided. One of them is predicting values with k-nearest neighbors algorithm and the other is optimizing the parameters k and d of the algorithm. These are carried out in parallel using multiple threads.
Maintained by Daniel Bastarrica Lacalle. Last updated 5 years ago.
knearest-neighbor-algorithmparalleltime-series-forecasting
19.6 match 1 stars 2.70 score 8 scripts
bbbruce
nncc:Nearest Neighbors Matching of Case-Control Data
Provides nearest-neighbors matching and analysis of case-control data. Cui, Z., Marder, E. P., Click, E. S., Hoekstra, R. M., & Bruce, B. B. (2022) <doi:10.1097/EDE.0000000000001504>.
Maintained by Beau Bruce. Last updated 1 years ago.
19.3 match 2.70 score 3 scriptsbioc
scran:Methods for Single-Cell RNA-Seq Data Analysis
Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologynormalizationsequencingrnaseqsoftwaregeneexpressiontranscriptomicssinglecellclusteringbioconductor-packagehuman-cell-atlassingle-cell-rna-seqopenblascpp
3.8 match 41 stars 13.14 score 7.6k scripts 36 dependents
tnagler
kdecopula:Kernel Smoothing for Bivariate Copula Densities
Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling.
Maintained by Thomas Nagler. Last updated 7 years ago.
6.8 match 8 stars 5.63 score 31 scripts 1 dependents
jcatwood
nntmvn:Draw Samples of Truncated Multivariate Normal Distributions
Draw samples from truncated multivariate normal distribution using the sequential nearest neighbor (SNN) method introduced in "Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation" <doi:10.48550/arXiv.2406.17307>.
Maintained by Jian Cao. Last updated 1 months ago.
12.9 match 2.85 score 3 scriptsbioc
bluster:Clustering Algorithms for Bioconductor
Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologysoftwaregeneexpressiontranscriptomicssinglecellclusteringcpp
3.8 match 9.43 score 636 scripts 51 dependents
toduckhanh
bcROCsurface:Bias-Corrected Methods for Estimating the ROC Surface of Continuous Diagnostic Tests
The bias-corrected estimation methods for the receiver operating characteristics ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) assumption.
Maintained by Duc-Khanh To. Last updated 1 years ago.
7.1 match 3.45 score 14 scriptsbioc
nullranges:Generation of null ranges via bootstrapping or covariate matching
Modular package for generation of sets of ranges representing the null hypothesis. These can take the form of bootstrap samples of ranges (using the block bootstrap framework of Bickel et al 2010), or sets of control ranges that are matched across one or more covariates. nullranges is designed to be inter-operable with other packages for analysis of genomic overlap enrichment, including the plyranges Bioconductor package.
Maintained by Michael Love. Last updated 5 months ago.
visualizationgenesetenrichmentfunctionalgenomicsepigeneticsgeneregulationgenetargetgenomeannotationannotationgenomewideassociationhistonemodificationchipseqatacseqdnaseseqrnaseqhiddenmarkovmodelbioconductorbootstrapgenomicsmatchingstatistics
2.7 match 27 stars 8.16 score 50 scripts 1 dependents
brandmaier
pdc:Permutation Distribution Clustering
Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.
Maintained by Andreas M. Brandmaier. Last updated 2 years ago.
3.5 match 6 stars 5.61 score 25 scripts 9 dependents
pmontman
TSclust:Time Series Clustering Utilities
A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.
Maintained by Pablo Montero Manso. Last updated 5 years ago.
3.3 match 2 stars 5.76 score 170 scripts 8 dependentsbioc
ANF:Affinity Network Fusion for Complex Patient Clustering
This package is used for complex patient clustering by integrating multi-omic data through affinity network fusion.
Maintained by Tianle Ma. Last updated 5 months ago.
clusteringgraphandnetworknetwork
3.3 match 4.30 score 9 scripts
cran
noisemodel:Noise Models for Classification Datasets
Implementation of models for the controlled introduction of errors in classification datasets. This package contains the noise models described in Saez (2022) <doi:10.3390/math10203736> that allow corrupting class labels, attributes and both simultaneously.
Maintained by José A. Sáez. Last updated 2 years ago.
7.0 match 2.00 scorebioc
CGEN:An R package for analysis of case-control studies in genetic epidemiology
This is a package for analysis of case-control data in genetic epidemiology. It provides a set of statistical methods for evaluating gene-environment (or gene-genes) interactions under multiplicative and additive risk models, with or without assuming gene-environment (or gene-gene) independence in the underlying population.
Maintained by Justin Lee. Last updated 5 months ago.
snpmultiplecomparisonclusteringfortran
3.6 match 3.90 score 10 scriptscran
Tlasso:Non-Convex Optimization and Statistical Inference for Sparse Tensor Graphical Models
An optimal alternating optimization algorithm for estimation of precision matrices of sparse tensor graphical models, and an efficient inference procedure for support recovery of the precision matrices.
Maintained by Xiang Lyu. Last updated 3 years ago.
3.6 match 1 stars 3.23 score 28 scripts 2 dependentscran
evclust:Evidential Clustering
Various clustering algorithms that produce a credal partition, i.e., a set of Dempster-Shafer mass functions representing the membership of objects to clusters. The mass functions quantify the cluster-membership uncertainty of the objects. The algorithms are: Evidential c-Means, Relational Evidential c-Means, Constrained Evidential c-Means, Evidential Clustering, Constrained Evidential Clustering, Evidential K-nearest-neighbor-based Clustering, Bootstrap Model-Based Evidential Clustering, Belief Peak Evidential Clustering, Neural-Network-based Evidential Clustering.
Maintained by Thierry Denoeux. Last updated 1 years ago.
4.6 match 2.48 score 1 dependents
lmjl-alea
squat:Statistics for Quaternion Temporal Data
An implementation of statistical tools for the analysis of rotation-valued time series and functional data. It relies on pre-existing quaternion data structure provided by the 'Eigen' 'C++' library.
Maintained by Aymeric Stamm. Last updated 1 years ago.
3.8 match 2 stars 3.00 score 6 scriptscran
dixon:Nearest Neighbour Contingency Table Analysis
Function to test spatial segregation and association based in contingency table analysis of nearest neighbour counts following Dixon (2002) <doi:10.1080/11956860.2002.11682700>. Some 'Fortran' code has been included to the original dixon2002() function of the 'ecespa' package to improve speed.
Maintained by Marcelino de la Cruz Rot. Last updated 1 years ago.
6.9 match 1.48 score 1 dependents
cristiano-pereira
nna:Nearest-Neighbor Analysis
Calculates spatial pattern analysis using a T-square sample procedure. This method is based on two measures "x" and "y". "x" - Distance from the random point to the nearest individual. "y" - Distance from individual to its nearest neighbor. This is a methodology commonly used in phytosociology or marine benthos ecology to analyze the species' distribution (random, uniform or clumped patterns). Ludwig & Reynolds (1988, ISBN:0471832359).
Maintained by Cristiano Pereira. Last updated 7 years ago.
8.0 match 1.00 score 1 scriptsbioc
nnSVG:Scalable identification of spatially variable genes in spatially-resolved transcriptomics data
Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more spatial locations.
Maintained by Lukas M. Weber. Last updated 19 days ago.
spatialsinglecelltranscriptomicsgeneexpressionpreprocessing
1.0 match 17 stars 7.75 score 183 scripts 1 dependents
dfsp-spirit
haze:Smoothing of per-Vertex Data on Triangular Meshes
Smoothing of per-vertex data on triangular meshes, sub mesh creation based on vertex indices, per-vertex data interpolation based on k-d trees.
Maintained by Tim Schäfer. Last updated 2 years ago.
per-vertexsmoothingtriangular-meshcpp
3.3 match 5 stars 2.40 scorecran
ecespa:Functions for Spatial Point Pattern Analysis
Some wrappers, functions and data sets for for spatial point pattern analysis (mainly based on 'spatstat'), used in the book "Introduccion al Analisis Espacial de Datos en Ecologia y Ciencias Ambientales: Metodos y Aplicaciones" and in the papers by De la Cruz et al. (2008) <doi:10.1111/j.0906-7590.2008.05299.x> and Olano et al. (2009) <doi:10.1051/forest:2008074>.
Maintained by Marcelino de la Cruz Rot. Last updated 2 years ago.
3.4 match 2.08 score 40 scripts 1 dependents
bioc
SpotSweeper:Spatially-aware quality control for spatial transcriptomics
Spatially-aware quality control (QC) software for both spot-level and artifact-level QC in spot-based spatial transcripomics, such as 10x Visium. These methods calculate local (nearest-neighbors) mean and variance of standard QC metrics (library size, unique genes, and mitochondrial percentage) to identify outliers spot and large technical artifacts.
Maintained by Michael Totty. Last updated 3 months ago.
softwarespatialtranscriptomicsqualitycontrolgeneexpressionbioconductorquality-controlspatial-transcriptomics
1.0 match 5 stars 6.73 score 77 scriptsbioc
concordexR:Identify Spatial Homogeneous Regions with concordex
Spatial homogeneous regions (SHRs) in tissues are domains that are homogenous with respect to cell type composition. We present a method for identifying SHRs using spatial transcriptomics data, and demonstrate that it is efficient and effective at finding SHRs for a wide variety of tissue types. concordex relies on analysis of k-nearest-neighbor (kNN) graphs. The tool is also useful for analysis of non-spatial transcriptomics data, and can elucidate the extent of concordance between partitions of cells derived from clustering algorithms, and transcriptomic similarity as represented in kNN graphs.
Maintained by Kayla Jackson. Last updated 2 months ago.
singlecellclusteringspatialtranscriptomics
1.0 match 13 stars 6.23 score 13 scriptsbioc
clst:Classification by local similarity threshold
Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons.
Maintained by Noah Hoffman. Last updated 5 months ago.
1.1 match 3.78 score 10 scripts 1 dependents