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R: Model-Based Clustering and Classification with the Multivariate t Distribution
...Classification with the Multivariate t Distribution Documentation for package ‘teigen’ version 2.2.2 DESCRIPTION file. Help Pages teigen-package teigen: Model-Based Clustering and Classification...
/CRAN/refmans/teigen/html/00Index.html
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R: Mixture Models for Clustering and Classification
...for Clustering and Classification Documentation for package ‘mixture’ version 2.1.1 DESCRIPTION file. Help Pages mixture-package Mixture Models for Clustering and Classification ARI Adjusted Rand...
/CRAN/refmans/mixture/html/00Index.html
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R: Model-Based Clustering and Classification for Longitudinal Data
...Clustering and Classification for Longitudinal Data longclust Model-Based Clustering and Classification for Longitudinal Data longclustEM Model-Based Clustering and Classification for Longitudinal...
/CRAN/refmans/longclust/html/00Index.html
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R: Variable Selection for Clustering and Classification
...print.vscc Printing for VSCC summary.vscc Summary for VSCC Objects vscc Variable Selection for Clustering and Classification vsccmanly Variable Selection for Skewed Clustering and Classification
/CRAN/refmans/vscc/html/00Index.html
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R: Classification and Clustering of Sequencing Data Based on a Poisson Model
...Classification and clustering of RNA sequencing data using a Poisson model Classify Classify observations using a Poisson model. Classify.cv Function to do cross-validation for Poisson classification.
/CRAN/refmans/PoiClaClu/html/00Index.html
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R: teigen: Model-Based Clustering and Classification with the...
...under a clustering or classification paradigm. Details Package: teigen Type: Package Version: 2.2.2 Date: 2018-02-15 License: GPL (>=2) LazyLoad: yes Author(s) Jeffrey L. Andrews, Jaymeson R. Wickins...
/CRAN/refmans/teigen/html/teigen-package.html
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R: Graphical Toolbox for Clustering and Classification of Data Frames
...clustering computeSupervised Supervised classification computeUnSupervised Unsupervised clustering extractProtos Prototypes extraction formatLabelSample Labels formatting imgClassif Images clustering ...
/CRAN/refmans/RclusTool/html/00Index.html
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R: Compare Two Classifications or Clustering Solutions of Varying Structure
...class_entropy Calculate cluster entropy per class class_purity Calculate cluster purity per class get_conf_mat Generate a confusion matrix from two classifications/clustering solutions. get_hard...
/CRAN/refmans/c2c/html/00Index.html
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R: Classification and clustering of RNA sequencing data using a...
PoiClaClu-package {PoiClaClu} R Documentation Classification and clustering of RNA sequencing data using a Poisson model Description A simple approach for performing classification and clustering...
/CRAN/refmans/PoiClaClu/html/PoiClaClu-package.html
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R: ROC Analysis in Three-Class Classification Problems for Clustered Data
...Classification Problems for Clustered Data ci_clus_vus Confidence Intervals for Covariate-specific VUS ClusROC ROC Analysis in Three-Class Classification Problems for Clustered Data clus_lme Linear...
/CRAN/refmans/ClusROC/html/00Index.html
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R: Clustering and Classification Inference with U-Statistics
Clustering and Classification Inference with U-Statistics Documentation for package ‘uclust’ version 1.0.0 DESCRIPTION file. Package NEWS. Help Pages bn Computes Bn Statistic. bn3 Computes Bn...
/CRAN/refmans/uclust/html/00Index.html
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R: Weighted k-Nearest Neighbors Classification and Clustering
...Classification and Clustering Description Weighted k-Nearest Neighbors Classification, Regression and spectral Clustering The complete list of functions can be displayed with library(help = kknn).
/CRAN/refmans/kknn/html/kknn-package.html
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R: Re-order Clusters in a Classification
...Clusters in a Classification Description In it's simplest form simply reassigns cluster numbers in an existing classification to re-order tables and graphs. Can also be used to combine clusters into...
/CRAN/refmans/optpart/html/reordclust.html
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R: Variable Selection for Clustering and Classification
...Selection for Clustering and Classification Description Performs variable selection under a clustering or classification framework. Automated implementation using model-based clustering is based on...
/CRAN/refmans/vscc/html/vscc-package.html
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R: Cluster centers of a classification
...classification. Function clustmedoid determines the medoid (object whose average dissimilarity to all the other objects is minimal) for each cluster in the classification. Usage clustcentroid(x, y, m...
/CRAN/refmans/vegclust/html/clustcentroid.html
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R: Mixture Models for Clustering and Classification
...clustering models for finite mixtures with components that are Gaussian, generalized hyperbolic, variance-gamma, Student's t, or skew-t, for model-based clustering and model-based classification, even...
/CRAN/refmans/mixture/html/mixture.html
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R: Model-Based Clustering and Classification for Longitudinal...
...Clustering and Classification for Longitudinal Data Description This is a package for clustering or classification of longitudinal data based on a mixture of multivariate t or Gaussian distributions...
/CRAN/refmans/longclust/html/longclust-package.html
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R: Classification, Regression, Clustering with K Nearest Neighbors
Package NEWS. Help Pages distance Calculate the distance between two vectors. knn Classification, regression, and clustering with k nearest neighbors. neighbr neighbr: A package for computing nearest...
/CRAN/refmans/neighbr/html/00Index.html
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R: classification variable
...classification variable Description Recodes the binary and row-stochastic membership matrix U into the classification variable (similar to the "cluster" output returned by kmeans()). Usage cluster(U)...
/CRAN/refmans/drclust/html/cluster.html
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R: Classification with Wilma's Clusters
...aggtrees (aggregated trees) are used for binary classification with the cluster representatives of Wilma's output. Usage dlda (xlearn, xtest, ylearn) nnr (xlearn, xtest, ylearn) logreg (xlearn, xtest...
/CRAN/refmans/supclust/html/dlda.html
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R: Merge Specified Clusters in a Classification
...Merge Specified Clusters in a Classification Description Re-assigns members of one cluster to another specified cluster, reducing the number of clusters by one. Usage mergeclust(clustering,from...
/CRAN/refmans/optpart/html/mergeclust.html
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R: Create Classification for Cluster.. functions
...Create Classification for Cluster.. functions Description Creates a Cls from arbitrary list of objects Usage ClusterCreateClassification(Objects,Decreasing) Arguments Objects Listed objects...
/CRAN/refmans/FCPS/html/ClusterCreateClassification.html
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R: High Dimensional Supervised Classification and Clustering
...Classification and Clustering Documentation for package ‘HDclassif’ version 2.2.1 DESCRIPTION file. Code demos. Use demo() to run them. Package NEWS. Help Pages HDclassif-package High Dimensional...
/CRAN/refmans/HDclassif/html/00Index.html
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R: Variable Selection for Clustering and Classification
...Selection for Clustering and Classification Description Performs variable selection under a clustering or classification framework. Automated implementation using model-based clustering is based on...
/CRAN/refmans/vscc/html/vscc.html
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R: Compute a linear discriminant analysis on classified cluster...
...on classified cluster groups Description Computes linear discriminant analysis (LDA) on classified cluster groups, and determines the goodness of classification for each cluster group. See MASS::lda...
/CRAN/refmans/parameters/html/cluster_discrimination.html
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R: Cluster classifications for local indicators of spatial...
hotspot {spdep} R Documentation Cluster classifications for local indicators of spatial association Description Used to return a factor showing so-called cluster classification for local indicators...
/CRAN/refmans/spdep/html/hotspotmap.html
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R: Subspace clustering based local classification using ORCLUS.
...clustering based local classification using ORCLUS. Description Assigns clusters and distances and classes for new data according to the intrinsic subspace clusters of an orclass classification model.
/CRAN/refmans/orclus/html/predict.orclass.html
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R: Clustering and Classification with the Contaminated Normal
Clustering and Classification with the Contaminated Normal Documentation for package ‘ContaminatedMixt’ version 1.3.8 DESCRIPTION file. Help Pages ContaminatedMixt-package ContaminatedMixt...
/CRAN/refmans/ContaminatedMixt/html/00Index.html
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R: Classification and Clustering of Preference Rankings
Classification and Clustering of Preference Rankings Documentation for package ‘ConsRankClass’ version 1.0.1 DESCRIPTION file. Help Pages cca K-Median Cluster Component Analysis ccacontrol Utility...
/CRAN/refmans/ConsRankClass/html/00Index.html
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R: Mixtures of Power Exponential and Skew Power Exponential Distributions for Use in Model-Based Clustering and Classification
...Clustering and Classification Documentation for package ‘mixSPE’ version 0.9.2 DESCRIPTION file. Package NEWS. Help Pages mixSPE-package Mixtures of skew power exponential or power exponential...
/CRAN/refmans/mixSPE/html/00Index.html
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R: Plot Rank Abundance Curve of classification results
...the clustering results from define_rb(). Usage plot_ulrb_clustering( data, sample_id = NULL, taxa_col, plot_all = FALSE, samples_col = "Sample", classification_col = "Classification", abundance_col...
/CRAN/refmans/ulrb/html/plot_ulrb_clustering.html
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R: Subspace clustering based local classification using ORCLUS.
...Subspace clustering based local classification using ORCLUS. Description Function to perform local classification where the subclasses are concentrated in different subspaces of the data. Usage...
/CRAN/refmans/orclus/html/orclass.html
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R: Classification description
...Classification description Description Realise the hierachical ascending classification (HCPC function) of the individuals (or rows) and describe the specifications of each cluster. Usage classif(res...
/CRAN/refmans/FactoInvestigate/html/classif.html
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R: Model-Based Clustering and Classification for Longitudinal...
...Clustering and Classification for Longitudinal Data Description Carries out model-based clustering or classification using multivariate t or Gaussian mixture models with Cholesky decomposed covariance...
/CRAN/refmans/longclust/html/longclustEM.html
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R: Naive Bayes Classification Learner
...be instantiated via the dictionary mlr_learners or with the associated sugar function lrn(): mlr_learners$get("classif.naive_bayes") lrn("classif.naive_bayes") Meta Information Task type: “classif”...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.naive_bayes.html
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R: Debug Measure for Classification
...for Classification Description This measure returns the number of observations in the PredictionClassif object. Its main purpose is debugging. The parameter na_ratio (numeric(1)) controls the ratio...
/CRAN/refmans/mlr3/html/mlr_measures_debug_classif.html
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R: Classification Tree Learner
...Classification Tree Learner Description A LearnerClassif for a classification tree implemented in rpart::rpart() in package rpart. Initial parameter values Parameter xval is initialized to 0 in order...
/CRAN/refmans/mlr3/html/mlr_learners_classif.rpart.html
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R: Classification, regression, and clustering with k nearest...
...Classification, regression, and clustering with k nearest neighbors. Description Classification, regression, and clustering with k nearest neighbors. Usage knn( train_set, test_set, k = 3...
/CRAN/refmans/neighbr/html/knn.html
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R: Hierarchic Classification by Ward's Method
ward.cluster {FactoClass} R Documentation Hierarchic Classification by Ward's Method Description Performs the classification by Ward's method from the matrix of Euclidean distances. Usage ward.cluster...
/CRAN/refmans/FactoClass/html/ward.cluster.html
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R: Finite Mixture Modeling, Clustering & Classification
Finite Mixture Modeling, Clustering & Classification Documentation for package ‘rebmix’ version 2.15.0 DESCRIPTION file. User guides, package vignettes and other documentation. Code demos. Use demo...
/CRAN/refmans/rebmix/html/00Index.html
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R: Clustering Object
...A clustering object is a list with a component called ‘clustering’ which is an integer vector of length n where n is the number of elements in a classification. Details The clustering object...
/CRAN/refmans/optpart/html/clustering.html
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R: Cost-sensitive Classification Measure
mlr_measures_classif.costs {mlr3} R Documentation Cost-sensitive Classification Measure Description Uses a cost matrix to create a classification measure. True labels must be arranged in columns...
/CRAN/refmans/mlr3/html/mlr_measures_classif.costs.html
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R: Featureless Classification Learner
...Featureless Classification Learner Description A simple LearnerClassif which only analyzes the labels during train, ignoring all features. Hyperparameter method determines the mode of operation during...
/CRAN/refmans/mlr3/html/mlr_learners_classif.featureless.html
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R: Quadratic Discriminant Analysis Classification Learner
mlr_learners_classif.qda {mlr3learners} R Documentation Quadratic Discriminant Analysis Classification Learner Description Quadratic discriminant analysis. Calls MASS::qda() from package MASS. Details...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.qda.html
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R: Linear Discriminant Analysis Classification Learner
...Classification Learner Description Linear discriminant analysis. Calls MASS::lda() from package MASS. Details Parameters method and prior exist for training and prediction but accept different values...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.lda.html
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R: Find an optimal classification among competing clustering...
find_optimal {optimus} R Documentation Find an optimal classification among competing clustering solutions Description find_optimal takes a clustering solution, or a set of related clustering solutions...
/CRAN/refmans/optimus/html/find_optimal.html
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R: Clustering the classification trees in a forest based on...
clusterforest {C443} R Documentation Clustering the classification trees in a forest based on similarities Description A function to get insight into a forest of classification trees by clustering the...
/CRAN/refmans/C443/html/clusterforest.html
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R: Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions
...Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions Documentation for package ‘MixGHD’ version 2.3.7 DESCRIPTION file. Help Pages ARI...
/CRAN/refmans/MixGHD/html/00Index.html
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R: Computes clusters by unsupervised OPF
opf_cluster {LibOPF} R Documentation Computes clusters by unsupervised OPF Description Computes clusters by unsupervised OPF Usage opf_cluster(dataSet, kmax, calculateOp, value, precomputedDistance...
/CRAN/refmans/LibOPF/html/opf_cluster.html
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R: Classification Neural Network Learner
...instantiated via the dictionary mlr_learners or with the associated sugar function lrn(): mlr_learners$get("classif.nnet") lrn("classif.nnet") Meta Information Task type: “classif” Predict Types: ...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.nnet.html
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R: Create a classification, regression, survival, cluster,...
...Create a classification, regression, survival, cluster, cost-sensitive classification or multilabel task. Description The task encapsulates the data and specifies - through its subclasses - the type...
/CRAN/refmans/mlr/html/Task.html
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R: Variable Selection for Skewed Clustering and Classification
...for Skewed Clustering and Classification Description Performs variable selection under a clustering framework. Accounts for mixtures of non-Gaussian distributions via the ManlyTransform (via 'ManlyMix').
/CRAN/refmans/vscc/html/vsccmanly.html
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R: k-Nearest-Neighbor Classification Learner
...or with the associated sugar function lrn(): mlr_learners$get("classif.kknn") lrn("classif.kknn") Meta Information Task type: “classif” Predict Types: “response”, “prob” Feature Types: ...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.kknn.html
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R: Model-Based Clustering & Classification Using PGMMs
pgmmEM {pgmm} R Documentation Model-Based Clustering & Classification Using PGMMs Description Carries out model-based clustering or classification using parsimonious Gaussian mixture models. AECM...
/CRAN/refmans/pgmm/html/pgmmEM.html
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R: Calculate clustering metrics for a confusion matrix
...clustering metrics for a confusion matrix Description Calculate a range of clustering metrics on a confusion confusion matrix, usually from get_conf_mat. Usage calculate_clustering_metrics(conf_mat)...
/CRAN/refmans/c2c/html/calculate_clustering_metrics.html
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R: External Cluster Validity Metrics
...Cluster Validity Metrics Description Computes four popular external cluster validity metrics (adjusted Rand index, purity, V-measure and Normalised Mutual Information) through comparison of cluster...
/CRAN/refmans/PPCI/html/cluster_performance.html
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R: Change mode of a cluster specification
...a cluster specification Usage ## S3 method for class 'cluster_spec' set_mode(object, mode) Arguments object A model specification. mode A character string for the model type (e.g. "classification" or...
/CRAN/refmans/tidyclust/html/set_mode.cluster_spec.html
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R: Logistic Regression Classification Learner
...Logistic Regression Classification Learner Description Classification via logistic regression. Calls stats::glm() with family set to "binomial". Internal Encoding Starting with mlr3 v0.5.0, the order...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.log_reg.html
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R: Classification Learner for Debugging
...Classification Learner for Debugging Description A simple LearnerClassif used primarily in the unit tests and for debugging purposes. If no hyperparameter is set, it simply constantly predicts...
/CRAN/refmans/mlr3/html/mlr_learners_classif.debug.html
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R: Semi-Supervised Classification, Regression and Clustering Methods
...Classification, Regression and Clustering Methods Documentation for package ‘SSLR’ version 0.9.3.3 DESCRIPTION file. User guides, package vignettes and other documentation. Code demos. Use demo...
/CRAN/refmans/SSLR/html/00Index.html
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R: Ranger Classification Learner
...Ranger Classification Learner Description Random classification forest. Calls ranger::ranger() from package ranger. Custom mlr3 parameters mtry: This hyperparameter can alternatively be set via our...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.ranger.html
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R: Clustering Evaluation Index Based on Known Ground Truth
cluster.evaluation {TSclust} R Documentation Clustering Evaluation Index Based on Known Ground Truth Description Computes the similarity between the true cluster solution and the one obtained...
/CRAN/refmans/TSclust/html/cluster.evaluation.html
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R: Cluster 1.0 markers into correct homologues per linkage group
...correct classification of homologues. Usually there are more clusters of (pseudo)homologues than expected. This function lets you inspect every linkage group separately and allows for clustering at a...
/CRAN/refmans/polymapR/html/cluster_per_LG.html
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R: Unsupervised Classification
...The classification method to use. One of "kmeans", "bclust". ... Further arguments for the classification method Details A clustering algorithm is applied to find clusters in the comparison patterns.
/CRAN/refmans/RecordLinkage/html/classifyUnsup.html
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R: GLM with Elastic Net Regularization Classification Learner
...cv_glmnet {mlr3learners} R Documentation GLM with Elastic Net Regularization Classification Learner Description Generalized linear models with elastic net regularization. Calls glmnet::cv.glmnet...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.cv_glmnet.html
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R: Conduct classification for subgroups.
...Conduct classification for subgroups. Description The classification model is conducted based on the BaCIS method and the subgroupos are classified into two clusters: high respone rate cluster and low...
/CRAN/refmans/bacistool/html/bacisClassification.html
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R: Cluster analysis for cognitive diagnosis based on the...
cd.cluster {ACTCD} R Documentation Cluster analysis for cognitive diagnosis based on the Asymptotic Classification Theory Description cd.cluster is used to classify examinees into unlabeled clusters...
/CRAN/refmans/ACTCD/html/cd.cluster.html
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R: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
...Q R S T U W mclust-package Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation -- A -- acidity Acidity data adjustedRandIndex Adjusted Rand Index as.hclust.hc...
/CRAN/refmans/mclust/html/00Index.html
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R: Evaluate DSM on Clustering Task (wordspace)
...Performs evaluation on a word clustering task by comparing a flat clustering solution based on semantic distances with a gold classification. Usage eval.clustering(task, M, dist.fnc = pair.distances...
/CRAN/refmans/wordspace/html/eval_clustering.html
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R: Cluster Analysis
...Cluster Analysis Description Compute hierarchical or kmeans cluster analysis and return the group assignment for each observation as vector. Usage cluster_analysis( x, n = NULL, method = "kmeans"...
/CRAN/refmans/parameters/html/cluster_analysis.html
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R: Performs the fuzzy clustering algorithm of He and Tan (2020).
...clustering algorithm of He and Tan (2020). Description vpca_clustering performs the fuzzy clustering algorithm proposed by He and Tan (2018). Usage vpca_clustering( X, k, m, var_rate = 0.9, max_it...
/CRAN/refmans/mlmts/html/vpca_clustering.html
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R: Refining a Classification by Re-Assigning Memberships
...Refining a Classification by Re-Assigning Memberships Description Refine allows you to re-assign specific elements of a classification from one class or cluster to another. In the default case, you...
/CRAN/refmans/optpart/html/refine.html
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R: Determination of optimal clustering procedure for a data set
...clustering procedure for a data set by varying all combinations of normalization formulas, distance measures, and clustering methods Usage cluster.Sim (x,p,minClusterNo,maxClusterNo,icq="S",outputHtml...
/CRAN/refmans/clusterSim/html/cluster.Sim.html
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R: Plot the posterior density of theta in the classification...
...tau1, tau2, phi1, phi2, clusterCutoff, MCNum, nDat, xDat, cols, seed) Arguments numGroup Number of subgroups in the trial. tau1 The precision parameter of subgroups clustering for the classification...
/CRAN/refmans/bacistool/html/bacisPlotClassification.html
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R: GLM with Elastic Net Regularization Classification Learner
mlr_learners_classif.glmnet {mlr3learners} R Documentation GLM with Elastic Net Regularization Classification Learner Description Generalized linear models with elastic net regularization. Calls glmnet...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.glmnet.html
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R: Classification Matching and Differencing
...(optionally) produces a new classification to reflect the congruences and differences Usage classmatch(x,y,type='full') Arguments x an object of class ‘clustering’, ‘partana’, ‘partition’...
/CRAN/refmans/optpart/html/classmatch.html
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R: Clustering and Model Selection with the Integrated Classification Likelihood
Clustering and Model Selection with the Integrated Classification Likelihood Documentation for package ‘greed’ version 0.6.1 DESCRIPTION file. User guides, package vignettes and other...
/CRAN/refmans/greed/html/00Index.html
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R: Asymptotic Classification Theory for Cognitive Diagnosis
...ACTCD ACTCD: Asymptotic Classification Theory for Cognitive Diagnosis alpha All possible attribute patterns cd.cluster Cluster analysis for cognitive diagnosis based on the Asymptotic Classification...
/CRAN/refmans/ACTCD/html/00Index.html
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R: Classification of paired comparison data
...classification Usage ClassifPaired(Data,Tcla) Arguments Data Object of class DataPairComp Tcla Number of classes to use for classification Details The function performs a hierarchical cluster analysis...
/CRAN/refmans/CompR/html/ClassifPaired.html
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R: Subspace Clustering Based on Arbitrarily Oriented Projected Cluster Generation
...Subspace clustering based local classification using ORCLUS. orclass.default Subspace clustering based local classification using ORCLUS. orclass.formula Subspace clustering based local classification...
/CRAN/refmans/orclus/html/00Index.html
cran-help matching:
classification, clustering and clustering |
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R: Compute the DIC value for the classification model.
...(numGroup, tau1, tau2, phi1, phi2, MCNum, nDat, xDat, seed) Arguments numGroup Number of subgroups in the trial. tau1 The precision parameter of subgroups clustering for the classification model. tau2...
/CRAN/refmans/bacistool/html/bacisCheckDIC.html
cran-help matching:
classification, classification and clustering |
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R: Classifications from Hierarchical Agglomeration
...gives the minimum index for observations in each of the two clusters merged at the ith stage of agglomerative hierarchical clustering. G An integer or vector of integers giving the number of clusters ...
/CRAN/refmans/mclust/html/hclass.html
cran-help matching:
classification, classification and clustering |
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R: Internal Cluster Validity Measures
...Cluster Validity Measures Description Implementation of a number of so-called cluster validity indices critically reviewed in (Gagolewski, Bartoszuk, Cena, 2021). See Section 2 therein and (Gagolewski...
/CRAN/refmans/genieclust/html/cluster_validity.html
cran-help matching:
classification, clustering, clustering and clustering |
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R: Optimizing Classification by Maximizing Dufrene and...
...Optimizing Classification by Maximizing Dufrene and Legendre's Indicator Value Description optindval is a iterative re-assignment classification algorithm that assigns samples to clusters to maximize...
/CRAN/refmans/optpart/html/optindval.html
cran-help matching:
classification, classification and clustering |
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R: Classification Validity Assessment by Table Deviance
...the clarity of the classification with respect to the original data, as opposed to a dissimilarity or distance matrix representation Usage ## Default S3 method: tabdev(x,clustering,nitr=999,...) ## S3...
/CRAN/refmans/optpart/html/tabdev.html
cran-help matching:
classification, classification and clustering |
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R: Implementing Methods for Spatial Fuzzy Unsupervised Classification
...NEWS. Help Pages adjustSpatialWeights Semantic adjusted spatial weights Arcachon SpatRaster of the bay of Arcachon barPlots Bar plots boot_group_validation Check the robustness of a classification by...
/CRAN/refmans/geocmeans/html/00Index.html
cran-help matching:
classification, classification and clustering |
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R: Extract the partition or the probabilities of classification
...of classification Description This function returns the probabilities of classification or the partition among the observations of an instance of VSLCMresults. Usage ## S4 method for signature...
/CRAN/refmans/VarSelLCM/html/fitted-methods.html
cran-help matching:
classification, classification and clustering |
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R: Extract the partition or the probabilities of classification
...of classification Description This function returns the probabilities of classification or the partition among the observations of an instance of VSLCMresults. Usage ## S4 method for signature...
/CRAN/refmans/VarSelLCM/html/fitted.values-methods.html
cran-help matching:
classification, classification and clustering |
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R: Variablewise statistics for clusters
cluster.varstats {fpc} R Documentation Variablewise statistics for clusters Description This function gives some helpful variable-wise information for cluster interpretation, given a clustering...
/CRAN/refmans/fpc/html/cluster.varstats.html
cran-help matching:
classification, clustering, clustering and clustering |
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R: Optimizing Classification by Minimizing Table Deviance
...Optimizing Classification by Minimizing Table Deviance Description opttdev is a iterative re-assignment classification algorithm that assigns samples to clusters to minimize the total deviance of a...
/CRAN/refmans/optpart/html/opttdev.html
cran-help matching:
classification, classification and clustering |
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R: ACTCD: Asymptotic Classification Theory for Cognitive...
...ACTCD: Asymptotic Classification Theory for Cognitive Diagnosis Description Cluster analysis for cognitive diagnosis based on the Asymptotic Classification Theory (Chiu, Douglas & Li, 2009). Details...
/CRAN/refmans/ACTCD/html/ACTCD-package.html
cran-help matching:
classification, classification and clustering |
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R: Complete groups membership with knn classification
...knn classification Description Starting with groups membership computed from a rainette2 clustering, every document not assigned to a cluster is reassigned using a k-nearest neighbour classification.
/CRAN/refmans/rainette/html/rainette2_complete_groups.html
cran-help matching:
classification, classification and clustering |
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R: Iteratively merges clusters in a way that improves predictive...
...Iteratively merges clusters in a way that improves predictive performance Description merge_clusters takes a clustering solution, generates all possible pairwise combinations of clusters, fits models...
/CRAN/refmans/optimus/html/merge_clusters.html
cran-help matching:
classification, clustering, clustering and clustering |
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R: Odds of correct classification (OCC)
...classification (OCC) Description Computes the odds of correct classification (OCC) for each cluster. In other words, it computes the proportion of trajectories that can be expected to be correctly...
/CRAN/refmans/latrend/html/OCC.html
cran-help matching:
classification, classification and clustering |
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R: Determine agreement of two classifications
...agreement on the diagonal of a contingency table comparing two classifications. Classifications need not have the same number of classes. Usage best.agreement(class1, class2, test = FALSE, rperm = 100)...
/CRAN/refmans/asbio/html/best.agreement.html
cran-help matching:
classification, classification and clustering |
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R: Extreme Gradient Boosting Classification Learner
...eXtreme Gradient Boosting classification. Calls xgboost::xgb.train() from package xgboost. If not specified otherwise, the evaluation metric is set to the default "logloss" for binary classification...
/CRAN/refmans/mlr3learners/html/mlr_learners_classif.xgboost.html
cran-help matching:
classification, classification, classification and clustering |
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R: Coefficients Comparing Classification Agreement
...table. match.names Flag whether row and columns should be matched by name. Details Suppose we want to compare two classifications summarized by the contingency table T=[t_{ij}] where i,j=1,\ldots,K...
/CRAN/refmans/e1071/html/classAgreement.html
cran-help matching:
classification, classification and clustering |
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R: Optimum Classification by Counts of Indicator Species
...Optimum Classification by Counts of Indicator Species Description Calculates the number of indicator species/cluster across a range of partitions Usage optimclass(comm, stride, pval = 0.01, counts = 2)...
/CRAN/refmans/optpart/html/optimclass.html
cran-help matching:
classification, classification and clustering |
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R: Match the groups obtained from two classifications
groups_matching {geocmeans} R Documentation Match the groups obtained from two classifications Description Match the groups obtained from two classifications based on the Jaccard index calculated on...
/CRAN/refmans/geocmeans/html/groups_matching.html
cran-help matching:
classification, classification and clustering |
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R: Classification Error Rate (CER)
...Classification Error Rate (CER) Description Compute the classification error rate of two partitions. Usage CER(ind, true.ind,nob=length(ind)) Arguments ind Vector, containing the cluster labels of...
/CRAN/refmans/RSKC/html/CER.html
cran-help matching:
classification, classification and clustering |