Package: RclusTool 0.91.6

Pierre-Alexandre Hebert

RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

Graphical toolbox for clustering and classification of data frames. It proposes a graphical interface to process clustering and classification methods on features data-frames, and to view initial data as well as resulted cluster or classes. According to the level of available labels, different approaches are proposed: unsupervised clustering, semi-supervised clustering and supervised classification. To assess the processed clusters or classes, the toolbox can import and show some supplementary data formats: either profile/time series, or images. These added information can help the expert to label clusters (clustering), or to constrain data frame rows (semi-supervised clustering), using Constrained spectral embedding algorithm by Wacquet et al. (2013) <doi:10.1016/j.patrec.2013.02.003> and the methodology provided by Wacquet et al. (2013) <doi:10.1007/978-3-642-35638-4_21>.

Authors:Guillaume Wacquet [aut], Pierre-Alexandre Hebert [aut, cre], Emilie Poisson [aut], Pierre Talon [aut]

RclusTool_0.91.6.tar.gz
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RclusTool.pdf |RclusTool.html✨
RclusTool/json (API)

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115 exports 0.00 score 125 dependencies 256 downloads

Last updated 7 months agofrom:1163374f5c. Checks:OK: 2. Indexed: yes.

Exports:abdPlotabdPlotTabsabdPlotTabsGUIaddClusteringaddIds2SamplingaddOperationanalyzePlotapplyPreprocessingbipartitionShibuildBatchTabbuildClusteringSamplebuildConstraintsMatrixbuildImportTabbuildNameOperationbuildPreprocessTabbuildSemisupTabbuildsupTabbuildUnsupTabclusterDensityclusterSummarycomputeCKmeanscomputeCSCcomputeEMcomputeGapcomputeGap2computeGaussianSimilaritycomputeGaussianSimilarityZPcomputeItemsSamplecomputeItemsSampleGUIcomputeKmeanscomputePcaNbDimscomputePcaSamplecomputeSamplingcomputeSemiSupervisedcomputeSpectralEmbeddingSamplecomputeSupervisedcomputeUnSupervisedconvNamesPairsToIndexPairsconvNamesToIndexcor.mtestcountItemscountItemsSampleGUIcreateResFoldercritMNCutdetailOperationdropTrainSetVarsElbowFinderElbowPlotextractFeaturesFromSummaryextractProtosfeatSpaceNameConvertFindNumberKformatLabelSampleformatParameterListguessFileEncodingimgClassifimportLabelSampleimportSampleinitBatchTabinitImportTabinitParametersinitPreprocessTabinitSemisupTabinitSupTabinitUnsupTabitemsModelKmeansAutoElbowKmeansQuickKwaySSSClistDerivableFeatureSpacesloadPreprocessFileloadPreviousResloadSampleloadSummaryMainWindowmakeFeatureSpaceOperationsmakeTitlematchNamesmeasureConstraintsOkmeasureMNCutmessageConsolenameClustersplotDensity2DplotProfileplotProfileExtractplotSampleFeaturespreviewCSVfilepurgeSampleRclusToolGUIreadTrainSetremoveZerossaveCalculsaveClusteringsaveCountssaveLogFilesaveManualProtossavePreprocesssaveSummarysearch.neighboursigClassifsortCharAsNumsortLabelspectralClusteringspectralClusteringNgspectralEmbeddingNgtk2add.notetabtk2delete.notetabtk2draw.notetabtk2notetab.RclusTooltkEmptyLinetkrplot.RclusTooltkrreplot.RclusTooltoStringDataFrameupdateClustersNamesvisualizeSampleClustering

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDataclasscliclustercolorspaceconclustcorrplotcowplotcpp11crosstalkdendextendDerivdigestdoBydplyrDTe1071ellipseemmeansestimabilityevaluatefactoextraFactoMineRfansifarverfastmapflashClustfontawesomefsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvisobandjpegjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmclustmdamemoisemgcvmicrobenchmarkmimeminqammandmodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpngpolynompromisesproxypurrrquantregR6randomForestrappdirsRColorBrewerRcppRcppEigenreshapereshape2rlangrmarkdownrstatixsassscalesscatterplot3dSearchTreesspSparseMstringistringrsurvivaltcltk2tibbletidyrtidyselecttinytextkrplotutf8vctrsviridisviridisLitewithrxfunyaml