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R: A Super K-Nearest Neighbor (SKNN) Classification Algorithm
...file. Help Pages SKNN-package Super K-Nearest Neighbor (SKNN) Classification Dist Finding the distance between two observations. KNN K-Nearest Neighbor Classification PCAy Revised PCA analysis PCAyd-...
/CRAN/refmans/SKNN/html/00Index.html
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R: k Nearest Neighbor Distances
...k Nearest Neighbor Distances Description Fast k-nearest neighbor distance searching algorithms. Usage knn.dist(data, k=10, algorithm=c("kd_tree", "cover_tree", "CR", "brute")) knnx.dist(data, query, k...
/CRAN/refmans/FNN/html/knn.dist.html
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R: Local k-nearest neighbor method for label ranking.
...Local k-nearest neighbor method for label ranking. Description Local k-nearest neighbor method with the parameter k determined using cross-validation error (defined as the sum of Kendall's distance).
/CRAN/refmans/pmr/html/local.knn.cv.html
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R: Fast and Scalable Approximate k-Nearest Neighbor Search Methods using 'N2' Library
...checkOpenMP boolean to check OpenMP exists crossKnn Perform fast approximate K-nearest neighbor search of rows input matrix mA in rows of matrix mB. Knn Perform fast approximate K-nearest neighbor...
/CRAN/refmans/N2R/html/00Index.html
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R: k-nearest neighbor denoising of a set of points
...k-nearest neighbor denoising of a set of points Description Reduce noise in a high-dimensional dataset by averaging each point with its nearby neighbors. Usage knnDenoise(X, block = rep(1, nrow(X)), k...
/CRAN/refmans/langevitour/html/knnDenoise.html
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R: K nearest neighbor model
...K nearest neighbor model Description A function to train a K nearest neighbor model to classify medulloblastoma subgroups using DNA methylation beta values (Illumina Infinium HumanMethylation450).
/CRAN/refmans/MBMethPred/html/KNearestNeighborModel.html
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R: Counting the number of each class in K nearest neighbor
...in K nearest neighbor Description The function to count how many neighbor of each instance belong to each class. Usage kncount(knidex, classArray) Arguments knidex The matrix of K nearest neighbor...
/CRAN/refmans/smotefamily/html/kncount.html
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R: Proportion-weighted k-nearest neighbor
...Proportion-weighted k-nearest neighbor Description It is a nearest-neighbor classifier adapted for working over quantification problems. This method applies a weighting scheme, reducing the weight on...
/CRAN/refmans/mlquantify/html/PWK.html
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R: K Nearest Neighbor Classifier
myknn {snn} R Documentation K Nearest Neighbor Classifier Description Implement the K nearest neighbor classification algorithm to predict the label of a new input using a training data set.
/CRAN/refmans/snn/html/myknn.html
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R: Local k-nearest neighbor method for label ranking.
...Local k-nearest neighbor method for label ranking. Description Predict the ranking of a group of judges based on a training dataset with rankings and covariates. First, for each judge, the k-nearest...
/CRAN/refmans/pmr/html/local.knn.html
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R: k Nearest Neighbor Regression
knn.reg {FNN} R Documentation k Nearest Neighbor Regression Description k-nearest neighbor regression Usage knn.reg(train, test = NULL, y, k = 3, algorithm=c("kd_tree", "cover_tree", "brute"))...
/CRAN/refmans/FNN/html/knn.reg.html
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R: Weighted k-Nearest Neighbor Model
KNNModel {MachineShop} R Documentation Weighted k-Nearest Neighbor Model Description Fit a k-nearest neighbor model for which the k nearest training set vectors (according to Minkowski distance) are...
/CRAN/refmans/MachineShop/html/KNNModel.html
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R: K Nearest Neighbor Classification
cla_knn {daltoolbox} R Documentation K Nearest Neighbor Classification Description Classifies using the K-Nearest Neighbor algorithm. It wraps the class library. Usage cla_knn(attribute, slevels, k = 1)...
/CRAN/refmans/daltoolbox/html/cla_knn.html
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R: Calculate and Plot k-Nearest Neighbor Distances
kNNdist {dbscan} R Documentation Calculate and Plot k-Nearest Neighbor Distances Description Fast calculation of the k-nearest neighbor distances for a dataset represented as a matrix of points.
/CRAN/refmans/dbscan/html/kNNdist.html
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R: nngeo: k-Nearest Neighbor Join for Spatial Data
...nngeo: k-Nearest Neighbor Join for Spatial Data Description K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C code from 'GeographicLib'...
/CRAN/refmans/nngeo/html/nngeo-package.html
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R: Wavelet Based K-Nearest Neighbor Model
Wavelet Based K-Nearest Neighbor Model Documentation for package ‘WaveletKNN’ version 0.1.0 DESCRIPTION file. Help Pages WaveletKNN Wavelet Based K-Nearest Neighbor Model
/CRAN/refmans/WaveletKNN/html/00Index.html
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R: k nearest neighbor algorithm for multi-variate data
...k nearest neighbor algorithm for multi-variate data Description k nearest neighbor algorithm for multi-variate data Usage knn(X, K = 2, init, Ninit = 50, verbose = FALSE, tol, Niter.max = 500)...
/CRAN/refmans/RBesT/html/knn.html
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R: K-Nearest Neighbor Classification
...K-Nearest Neighbor Classification Description It's implementation of the K-Nearest Neighbor classification method for data of any number of dimentions. Usage KNN(data, Class, k, test) Arguments...
/CRAN/refmans/SKNN/html/KNN.html
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R: Generalized k-Nearest Neighbor Classification
gknn {cba} R Documentation Generalized k-Nearest Neighbor Classification Description Compute the k-nearest neighbor classification given a matrix of cross-distances and a factor of class values.
/CRAN/refmans/cba/html/gknn.html
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R: Wavelet Based K-Nearest Neighbor Model
...K-Nearest Neighbor Model Description Wavelet Based K-Nearest Neighbor Model Usage WaveletKNN(ts, MLag = 12, split_ratio = 0.8, wlevels = 3) Arguments ts Time Series Data MLag Maximum Lags split_ratio...
/CRAN/refmans/WaveletKNN/html/WaveletKNN.html
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R: K-d tree based k nearest neighbor search
knn_meanShift {meanShiftR} R Documentation K-d tree based k nearest neighbor search Description knn_meanShift performs a search for the k nearest neighbors of a single point, where nearest...
/CRAN/refmans/meanShiftR/html/knn_meanShift.html
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R: k-Nearest Neighbor Join for Spatial Data
k-Nearest Neighbor Join for Spatial Data Documentation for package ‘nngeo’ version 0.4.8 DESCRIPTION file. User guides, package vignettes and other documentation. Package NEWS. Help Pages cities...
/CRAN/refmans/nngeo/html/00Index.html
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R: Super K-Nearest Neighbor (SKNN) Classification
...Super K-Nearest Neighbor (SKNN) Classification Description It's a Super K-Nearest Neighbor classification method with using kernel density to describe the weight of the distance between a training...
/CRAN/refmans/SKNN/html/SKNN-package.html
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R: Perform fast approximate K-nearest neighbor search on rows of...
...fast approximate K-nearest neighbor search on rows of the input matrix m. Description Perform fast approximate K-nearest neighbor search on rows of the input matrix m. Usage Knn( m, k, nThreads = 10L...
/CRAN/refmans/N2R/html/Knn.html
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R: Symbolic k-Nearest Neighbor Regression
...Symbolic k-Nearest Neighbor Regression Description Symbolic k-Nearest Neighbor Regression Usage sym.knn( formula, sym.data, method = c("cm", "crm"), scale = TRUE, kmax = 20, kernel = "triangular"...
/CRAN/refmans/RSDA/html/sym.knn.html
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R: Super K-Nearest Neighbor (SKNN) Classification
...K-Nearest Neighbor (SKNN) Classification Description It's a Super K-Nearest Neighbor classification method with using kernel density to describe weight of the distance between a training observation...
/CRAN/refmans/SKNN/html/SKNN.html
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R: Perform fast approximate K-nearest neighbor search of rows...
crossKnn {N2R} R Documentation Perform fast approximate K-nearest neighbor search of rows input matrix mA in rows of matrix mB. Description Perform fast approximate K-nearest neighbor search of rows...
/CRAN/refmans/N2R/html/crossKnn.html
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R: Spatial K nearest neighbor
...K nearest neighbor Description Find K nearest neighbors for two spatial objects Usage knn( y, x, k = 1, d = NULL, ids = NULL, weights.y = NULL, weights.x = NULL, indexes = FALSE ) Arguments y Spatial...
/CRAN/refmans/spatialEco/html/knn.html
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R: Calculate the K-Nearest Neighbor model domain applicability...
knn_domain_score {viraldomain} R Documentation Calculate the K-Nearest Neighbor model domain applicability score Description This function fits a K-Nearest Neighbor (KNN) model to the provided...
/CRAN/refmans/viraldomain/html/knn_domain_score.html
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R: K Nearest Neighbor Forecasting with a Tailored Similarity Metric
K Nearest Neighbor Forecasting with a Tailored Similarity Metric Documentation for package ‘knnwtsim’ version 1.0.0 DESCRIPTION file. Package NEWS. Help Pages boston_911dispatch_weekly...
/CRAN/refmans/knnwtsim/html/00Index.html
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R: Visualize SHAP Values for K-Nearest Neighbor Model
...K-Nearest Neighbor Model Description Visualizes SHAP (Shapley Additive Explanations) values for a KNN (K-Nearest Neighbor) model by employing the DALEXtra and DALEX packages to provide visual insights...
/CRAN/refmans/viralx/html/viralx_knn_vis.html
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R: K-Nearest Neighbor Hypergraph.
knn_hypergraph {HyperG} R Documentation K-Nearest Neighbor Hypergraph. Description A hypergraph is constructed from data in which each hyper-edge corresponds to a vertex and its k-nearest neighbors.
/CRAN/refmans/HyperG/html/knn_hypergraph.html
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R: k-nearest neighbor (kNN) supervised classification method
...k-nearest neighbor (kNN) supervised classification method Description Performs the k-nearest neighbor (kNN) supervised classification method. Usage knn(train, test, class, k = 1, dist = "euclidean"...
/CRAN/refmans/Kira/html/knn.html
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R: Weighted k-Nearest Neighbor Classifier
kknn {kknn} R Documentation Weighted k-Nearest Neighbor Classifier Description Performs k-nearest neighbor classification of a test set using a training set. For each row of the test set, the k nearest...
/CRAN/refmans/kknn/html/kknn.html
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R: Cross-validation for K nearest-neighbor regression
...K nearest-neighbor regression Description This function calculates the estimated cross-validation prediction error for K nearest-neighbor regression and returns a suitable choice for K. Usage cv_knn...
/CRAN/refmans/bcROCsurface/html/cv_knn.html
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R: Global Explainers for K-Nearest Neighbor Models
viralx_knn_glob {viralx} R Documentation Global Explainers for K-Nearest Neighbor Models Description This function calculates global feature importance for a K-Nearest Neighbors (KNN) model trained on...
/CRAN/refmans/viralx/html/viralx_knn_glob.html
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R: Explain K Nearest Neighbor Model using SHAP values
viralx_knn_shap {viralx} R Documentation Explain K Nearest Neighbor Model using SHAP values Description This function calculates SHAP (SHapley Additive exPlanations) values for a K-Nearest Neighbors...
/CRAN/refmans/viralx/html/viralx_knn_shap.html
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R: k-Nearest-Neighbor Regression Learner
...k-Nearest-Neighbor Regression Learner Description k-Nearest-Neighbor regression. Calls kknn::kknn() from package kknn. Initial parameter values store_model: See note. Dictionary This mlr3::Learner can...
/CRAN/refmans/mlr3learners/html/mlr_learners_regr.kknn.html
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R: k-Nearest-Neighbor Classification Learner
...k-Nearest-Neighbor Classification Learner Description k-Nearest-Neighbor classification. Calls kknn::kknn() from package kknn. Initial parameter values store_model: See note. Dictionary This mlr3...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.kknn.html
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R: Global Visualization of SHAP Values for K-Nearest Neighbor...
glob_knn_vis {viralx} R Documentation Global Visualization of SHAP Values for K-Nearest Neighbor Model Description This function generates a visualization for the global feature importance of a K-...
/CRAN/refmans/viralx/html/glob_knn_vis.html
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R: k-Nearest Neighbor Mutual Information Estimator
k-Nearest Neighbor Mutual Information Estimator Documentation for package ‘knnmi’ version 1.0 DESCRIPTION file. Help Pages cond_mutual_inf Conditional mutual information estimation mutual_info_df...
/CRAN/refmans/knnmi/html/00Index.html
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R: Embed a k-nearest neighbor (kNN) graph within a UMAP. Used...
embedKnnGraph {sccore} R Documentation Embed a k-nearest neighbor (kNN) graph within a UMAP. Used within embedGraphUmap(). Please see McInnes et al <doi:10.21105/joss.00861> for the UMAP...
/CRAN/refmans/sccore/html/embedKnnGraph.html
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R: Carry out a k-nearest neighbor classification on training...
vcr.knn.train {classmap} R Documentation Carry out a k-nearest neighbor classification on training data, and prepare to visualize its results. Description Carries out a k-nearest neighbor...
/CRAN/refmans/classmap/html/vcr.knn.train.html
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R: K nearest-neighbor (KNN) regression
...K nearest-neighbor (KNN) regression Description rho_knn uses the KNN approach to estimate the probabilities of the disease status in case of three categories. Usage rho_knn( x_mat, dise_vec, veri_stat...
/CRAN/refmans/bcROCsurface/html/rho_knn.html
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R: Saturated or K Nearest Neighbor Graph
...Saturated or K Nearest Neighbor Graph Description Creates a kNN or saturated graph SpatialLinesDataFrame object Usage knn.graph( x, row.names = NULL, k = NULL, max.dist = NULL, long.lat = FALSE, drop...
/CRAN/refmans/GeNetIt/html/knn.graph.html
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R: k-Nearest Neighbor classifier
perform.knn {stylo} R Documentation k-Nearest Neighbor classifier Description A machine-learning supervised classifier; this function is a wrapper for the k-NN procedure provided by the...
/CRAN/refmans/stylo/html/perform.knn.html
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R: Supervised classification using k-nearest neighbor
...Supervised classification using k-nearest neighbor Description Unified (formula-based) interface version of the k-nearest neighbor algorithm provided by class::knn(). Usage mlKnn(train, ...) ml_knn...
/CRAN/refmans/mlearning/html/mlKnn.html
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R: Carry out a k-nearest neighbor classification on new data,...
vcr.knn.newdata {classmap} R Documentation Carry out a k-nearest neighbor classification on new data, and prepare to visualize its results. Description Predicts class labels for new data by k nearest...
/CRAN/refmans/classmap/html/vcr.knn.newdata.html
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R: K-Nearest Neighbor for Protein (KNNProtein)
...K-Nearest Neighbor for Protein (KNNProtein) Description This function is like KNNPeptide with the difference that similarity score is computed by Needleman-Wunsch algorithm. Usage KNNProtein(seqs...
/CRAN/refmans/ftrCOOL/html/KNNProtein.html
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R: K-Nearest Neighbor for Peptides (KNNPeptide)
KNNPeptide {ftrCOOL} R Documentation K-Nearest Neighbor for Peptides (KNNPeptide) Description This function needs an extra training data set and a label. We compute the similarity score of each input...
/CRAN/refmans/ftrCOOL/html/KNNPeptide.html
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R: K-nearest neighbor SVD-Based GP model
...K-nearest neighbor SVD-Based GP model Description Fits a K-nearest neighbour SVD-based GP model on a test set X0, training set design and response matrix resp. The local neighbourhood sets consist of...
/CRAN/refmans/DynamicGP/html/knnsvdGP.html
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R: Package for Stabilized Nearest Neighbor Classifier
...classifiers, including K-nearest neighbor classifier, weighted nearest neighbor classifier, bagged nearest neighbor classifier, optimal weighted nearest neighbor classifier, and a new stabilized...
/CRAN/refmans/snn/html/snn-package.html
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R: Tuning via 5 fold Cross-Validation.
cv.tune {snn} R Documentation Tuning via 5 fold Cross-Validation. Description Implement the tuning procedure for K-nearest neighbor classifier, bagged nearest neighbor classifier, optimal weighted...
/CRAN/refmans/snn/html/cv.tune.html
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R: (Shared) Nearest-neighbor graph construction
...(via compute.SNN), construct a shared nearest neighbor graph by calculating the neighborhood overlap (Jaccard index) between every cell and its k.param nearest neighbors. Usage FindNeighbors(object...
/CRAN/refmans/Seurat/html/FindNeighbors.html
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R: Fast Nearest Neighbor Search Algorithms and Applications
...crossentropy Cross Entropy entropy Shannon Entropy get.knn Search Nearest Neighbors get.knnx Search Nearest Neighbors KL.dist Kullback-Leibler Divergence KL.divergence Kullback-Leibler Divergence KLx...
/CRAN/refmans/FNN/html/00Index.html
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R: Nearest Neighbor Graphs
...neighbor, k-nearest neighbor, and mutual k-nearest neighbor (di)graphs. Usage nng(x = NULL, dx = NULL, k = 1, mutual = FALSE, method = NULL, use.fnn = FALSE, algorithm = 'cover_tree') Arguments x a...
/CRAN/refmans/cccd/html/nng.html
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R: Weighted k-Nearest Neighbors
...Contrast Matrices contr.ordinal Contrast Matrices cv.kknn Training kknn glass Glass Identification Database ionosphere Johns Hopkins University Ionosphere Database kknn Weighted k-Nearest Neighbor...
/CRAN/refmans/kknn/html/00Index.html
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R: Search Nearest Neighbors
...Fast k-nearest neighbor searching algorithms including a kd-tree, cover-tree and the algorithm implemented in class package. Usage get.knn(data, k=10, algorithm=c("kd_tree", "cover_tree", "CR", "brute"))...
/CRAN/refmans/FNN/html/get.knn.html
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R: Merge multiple approximate nearest neighbors graphs
...nearest neighbor searches: the output will be at least as accurate as the most accurate of the two input graphs, and ideally will be more accurate than either. Usage merge_knn(graphs, is_query = FALSE, ...
/CRAN/refmans/rnndescent/html/merge_knn.html
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R: Jarvis-Patrick Clustering
...Jarvis-Patrick Clustering Description Fast C++ implementation of the Jarvis-Patrick clustering which first builds a shared nearest neighbor graph (k nearest neighbor sparsification) and then places...
/CRAN/refmans/dbscan/html/jpclust.html
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R: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms
...Superclass adjacencylist.frNN Find the Fixed Radius Nearest Neighbors adjacencylist.kNN Find the k Nearest Neighbors adjacencylist.NN NN - Nearest Neighbors Superclass as.dendrogram Coersions...
/CRAN/refmans/dbscan/html/00Index.html
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R: Search Nearest Neighbors
...k-nearest neighbor searching algorithms including a kd-tree, cover-tree and the algorithm implemented in class package. Usage knn.index(data, k=10, algorithm=c("kd_tree", "cover_tree", "CR", "brute"))...
/CRAN/refmans/FNN/html/knn.index.html
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R: Find nearest neighbors using nearest neighbor descent
...nnd_knn( data, k = NULL, metric = "euclidean", init = "rand", init_args = NULL, n_iters = NULL, max_candidates = NULL, delta = 0.001, low_memory = TRUE, weight_by_degree = FALSE, use_alt_metric = TRUE...
/CRAN/refmans/rnndescent/html/nnd_knn.html
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R: Build approximate nearest neighbors index and neighbor graph
...please see the other functions in the package. Usage rnnd_build( data, k = 30, metric = "euclidean", use_alt_metric = TRUE, init = "tree", n_trees = NULL, leaf_size = NULL, max_tree_depth = 200, ...
/CRAN/refmans/rnndescent/html/rnnd_build.html
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R: Stabilized Nearest Neighbor Classifier
...5 fold Cross-Validation. mybnn Bagged Nearest Neighbor Classifier mycis Classification Instability mydata Data Generator myerror Classification Error myknn K Nearest Neighbor Classifier myownn Optimal...
/CRAN/refmans/snn/html/00Index.html
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R: Explainers for Regression Models in HIV Research
...of SHAP Values for Cubist Rules Model glob_knn_vis Global Visualization of SHAP Values for K-Nearest Neighbor Model glob_nn_vis Global Visualization of SHAP Values for Neural Network Model train2...
/CRAN/refmans/viralx/html/00Index.html
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R: Project query into UMAP coordinates of a reference
...UMAP. This is essentially a wrapper around two steps: FindNeighbors - Find the nearest reference cell neighbors and their distances for each query cell. RunUMAP - Perform umap projection by providing...
/CRAN/refmans/Seurat/html/ProjectUMAP.html
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R: Find approximate nearest neighbors
...and complexity of the return value. Usage rnnd_knn( data, k = 30, metric = "euclidean", use_alt_metric = TRUE, init = "tree", n_trees = NULL, leaf_size = NULL, max_tree_depth = 200, margin = "auto"...
/CRAN/refmans/rnndescent/html/rnnd_knn.html
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R: Shared Nearest Neighbor Clustering
...Shared Nearest Neighbor Clustering Description Implements the shared nearest neighbor clustering algorithm by Ertoz, Steinbach and Kumar (2003). Usage sNNclust(x, k, eps, minPts, borderPoints = TRUE...
/CRAN/refmans/dbscan/html/sNNclust.html
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R: rnndescent: Nearest Neighbor Descent Method for Approximate...
...Dong and co-workers (2010) doi:10.1145/1963405.1963487. Based on the 'Python' package 'PyNNDescent' https://github.com/lmcinnes/pynndescent. Details The rnndescent package provides functions to create...
/CRAN/refmans/rnndescent/html/rnndescent-package.html
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R: Query an index for approximate nearest neighbors
...method of Iwasaki and Miyazaki (2018). For further control over the search effort, the total number of distance calculations can also be bounded, similar to the method of Harwood and Drummond (2016).
/CRAN/refmans/rnndescent/html/rnnd_query.html
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R: Query a search graph for nearest neighbors
...to build that graph. Usage graph_knn_query( query, reference, reference_graph, k = NULL, metric = "euclidean", init = NULL, epsilon = 0.1, max_search_fraction = 1, use_alt_metric = TRUE, n_threads = 0...
/CRAN/refmans/rnndescent/html/graph_knn_query.html
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R: Approximate nearest neighbor search routines
...or box-decomposition tree (bd-tree) for efficient k-nearest neighbor searches. Usage ann(ref, target, k=1, eps=0.0, tree.type="kd", search.type="standard", bucket.size=1, split.rule="sl_midpt", shrink...
/CRAN/refmans/yaImpute/html/ann.html
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R: Stabilized Nearest Neighbor Classifier
...set. The stabilized nearest neighbor classifier contains the K-nearest neighbor classifier and the optimal weighted nearest neighbor classifier as two special cases. Usage mysnn(train, test, lambda)...
/CRAN/refmans/snn/html/mysnn.html
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R: Find nearest neighbors using a random projection forest
...Returns the approximate k-nearest neighbor graph of a dataset by searching multiple random projection trees, a variant of k-d trees originated by Dasgupta and Freund (2008). Usage rpf_knn( data, k...
/CRAN/refmans/rnndescent/html/rpf_knn.html
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R: Kullback and entropy estimation from MCMC simulation output -...
...divergence between p^t and the target density, for t=1 up to the number of iterations that have been simulated. The MCMC simulations must be computed before or externally, and passed as a "plMCMC"...
/CRAN/refmans/EntropyMCMC/html/EntropyMCMC.html
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R: Optimal Weighted Nearest Neighbor Classification
...optimal weighting scheme for k nearest neighbor classification. The performance improvement is greatest when the dimension is 4 as reported in the reference. Usage ownn(train, test, cl, testcl=NULL, k...
/CRAN/refmans/FNN/html/ownn.html
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R: Machine Learning Algorithms with Unified Interface and Confusion Matrices
...‘mlearning’ version 1.2.1 DESCRIPTION file. Package NEWS. Help Pages mlearning-package Machine Learning Algorithms with Unified Interface and Confusion Matrices confusion Construct and analyze...
/CRAN/refmans/mlearning/html/00Index.html
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R: Recommended Learners for 'mlr3'
...Learner LearnerClassifGlmnet GLM with Elastic Net Regularization Classification Learner LearnerClassifKKNN k-Nearest-Neighbor Classification Learner LearnerClassifLDA Linear Discriminant Analysis...
/CRAN/refmans/mlr3learners/html/00Index.html
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R: k-Nearest-Neighbors Search
knn {mlpack} R Documentation k-Nearest-Neighbors Search Description An implementation of k-nearest-neighbor search using single-tree and dual-tree algorithms. Given a set of reference points and query...
/CRAN/refmans/mlpack/html/knn.html
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R: Nearest neighbor augmentatation based on ranks
...performs the nearest neighbor augmentation based on the rank of covariate values according to the scheme discribed on page 410-411 of Wang, Tolos and Wang (2010) Usage makepseudo(N, n, k, a, alltrt)...
/CRAN/refmans/PSSIM/html/makepseudo.html
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R: Local Nearest Neighbor (LNN) Entropy Estimator
...kernel and kNN selected bandwidth. Entropy is estimated by taking a Monte Carlo estimate using local kernel density estimate of the negative-log density. Usage lnn_entropy(data, k = 5, tr = 30, bw...
/CRAN/refmans/rmi/html/lnn_entropy.html
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R: Mutual Information Estimators
...on k-Nearest Neighbor and local density estimators. Currently, rmi provides the Kraskov et al. algorithm (KSG) 1 and 2, Local Non-uniformity Corrected (LNC) KSG, and the Local Nearest Neighbor (LNN)...
/CRAN/refmans/rmi/html/rmi.html
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R: kNN search
...{knn.covertree} R Documentation kNN search Description k nearest neighbor search with custom distance function. Usage find_knn(data, k, ..., query = NULL, distance = c("euclidean", "cosine", "rankcor")...
/CRAN/refmans/knn.covertree/html/knn.html
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R: Dixon (2002) Nearest-neighbor contingency table analysis
...of Dixon (2002) to test spatial segregation for several species by analyzing the counts of the nearest neighbour contingency table for a marked point pattern. Usage dixon2002(datos, nsim = 99)...
/CRAN/refmans/ecespa/html/dixon2002.html
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R: Local Nearest Neighbor (LNN) MI Estimator
...(LNN) mutual information estimator by Gao et al. 2017. This estimator uses the LNN entropy (lnn_entropy) estimator into the mutual information identity. Usage lnn_mi(data, splits, k = 5, tr = 30)...
/CRAN/refmans/rmi/html/lnn_mi.html
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R: Find Nearest Neighbors and Distances
...A k-nearest neighbor algorithm using the hnswlib library (https://github.com/nmslib/hnswlib). Usage hnsw_knn( X, k = 10, distance = "euclidean", M = 16, ef_construction = 200, ef = 10, verbose = FALSE...
/CRAN/refmans/RcppHNSW/html/hnsw_knn.html
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R: Calculate distance between two gene expression data sets
...sets Usage disteg( cross, pheno, pmark, min.genoprob = 0.99, k = 20, min.classprob = 0.8, classprob2drop = 1, repeatKNN = TRUE, max.selfd = 0.3, phenolabel = "phenotype", weightByLinkage = FALSE, map...
/CRAN/refmans/lineup/html/disteg.html
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R: K-nearest neighbors via kknn
...For this engine, there are multiple modes: classification and regression Tuning Parameters This model has 3 tuning parameters: neighbors: # Nearest Neighbors (type: integer, default: 5L) weight_func...
/CRAN/refmans/parsnip/html/details_nearest_neighbor_kknn.html
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R: Dixon (2002) Nearest-neighbor contingency table analysis
...Dixon (2002) to test spatial segregation for several species by analyzing the counts of the nearest neighbour contingency table for a marked point pattern. Usage dixon(datos, nsim = 99, fortran =TRUE)...
/CRAN/refmans/dixon/html/dixon.html
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R: Auxiliary function for computing S and the effect on S of the...
...structure: SAD, N, and aggregation Usage get_delta_curves( x, tests = c("SAD", "N", "agg"), spat_algo = NULL, inds = NULL, ind_dens = NULL, n_plots = NULL ) Arguments x can either be a: 1) mob_in...
/CRAN/refmans/mobr/html/get_delta_curves.html
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R: K-Approximate-Nearest-Neighbor Search with LSH
lsh {mlpack} R Documentation K-Approximate-Nearest-Neighbor Search with LSH Description An implementation of approximate k-nearest-neighbor search with locality-sensitive hashing (LSH). Given a set of...
/CRAN/refmans/mlpack/html/lsh.html
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R: Similarity Graph
...calculated using the merged fuzzy simplicial set approach in the Uniform Manifold Approximation and Projection (UMAP) method (McInnes et al., 2018), but the approach from LargeVis (Tang et al., 2016)...
/CRAN/refmans/uwot/html/similarity_graph.html
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R: Parallel simulation and Entropy estimation of MCMC's - single...
...MCMC's - single core and cluster versions Description This function simulates “parallel chains” (iid copies) of a MCMC algorithm, i.e. for each “time” iteration t the next step of all the nmc...
/CRAN/refmans/EntropyMCMC/html/EntropyParallel.html
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R: Imputation of missing values in compositional data using knn...
...several k-nearest neighbor methods for the imputation of missing values in compositional data. Usage impKNNa( x, method = "knn", k = 3, metric = "Aitchison", agg = "median", primitive = FALSE, normknn...
/CRAN/refmans/robCompositions/html/impKNNa.html
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R: Expansion of must-link and cannot-link constraints
...two attributes: a matrix ML containing nbML x 2 must-link constraints and a matrix CL containing nbCL x 2 cannot-link constraints. ind An n*k matrix containing the k nearest neighbor indices. distan...
/CRAN/refmans/evclust/html/expandlink.html
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R: The positive region based fuzzy-rough nearest neighbor...
...to implement the positive region based fuzzy-rough nearest neighbor algorithm (POSNN) which was proposed by (Verbiest et al, 2012) for predicting classes of new data. Usage C.POSNN.FRST(decision.table...
/CRAN/refmans/RoughSets/html/C.POSNN.FRST.html
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R: Calculates a mixing metric
...the k nearest neighbor and what rank that neighbor was in the overall neighborhood. We then take the median across all groups as the mixing metric per cell. Usage MixingMetric( object, grouping.var, ...
/CRAN/refmans/Seurat/html/MixingMetric.html
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R: Probability Models for Ranking Data
...statistics of a ranking dataset idea idea leisure.black leisure.black leisure.white leisure.white local.knn Local k-nearest neighbor method for label ranking. local.knn.cv Local k-nearest neighbor...
/CRAN/refmans/pmr/html/00Index.html
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R: Dimensionality Reduction with a LargeVis-like method
...n_epochs = -1, learning_rate = 1, scale = "maxabs", init = "lvrandom", init_sdev = NULL, repulsion_strength = 7, negative_sample_rate = 5, nn_method = NULL, n_trees = 50, search_k = 2 * n_neighbors...
/CRAN/refmans/uwot/html/lvish.html
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