# High-Quality Visualizations of Large, High-Dimensional Datasets

## Documentation for package ‘largeVis’ version 0.2.1.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

as.dendrogram.hdbscan | as.dendrogram.hdbscan
as.dist.edgematrix | Build an nearest-neighbor graph weighted by distance.
buildEdgeMatrix | Build an nearest-neighbor graph weighted by distance.
buildWijMatrix | buildWijMatrix
buildWijMatrix.CsparseMatrix | buildWijMatrix
buildWijMatrix.edgematrix | buildWijMatrix
buildWijMatrix.TsparseMatrix | buildWijMatrix
distance | Calculate pairwise Euclidean or angular distances efficiently
distance.CsparseMatrix | Calculate pairwise Euclidean or angular distances efficiently
distance.matrix | Calculate pairwise Euclidean or angular distances efficiently
distance.TsparseMatrix | Calculate pairwise Euclidean or angular distances efficiently
ggManifoldMap | Visualize an embedding by ggplotting with images
gplot | gplot
hdbscan | hdbscan
largeVis | Apply the LargeVis algorithm for visualizing large high-dimensional datasets.
lof | Local Outlier Factor Score
lv_dbscan | lv_dbscan
lv_optics | lv_optics
manifoldMap | Visualize an embedding by plotting with images
manifoldMapStretch | manifoldMapStretch
neighborsToVectors | A utility function to convert a k-NN graph to a pair of 0-indexed vectors of indices.
projectKNNs | Project a distance matrix into a lower-dimensional space.
randomProjectionTreeSearch | Find approximate k-Nearest Neighbors using random projection tree search.
randomProjectionTreeSearch.CsparseMatrix | Find approximate k-Nearest Neighbors using random projection tree search.
randomProjectionTreeSearch.matrix | Find approximate k-Nearest Neighbors using random projection tree search.
randomProjectionTreeSearch.TsparseMatrix | Find approximate k-Nearest Neighbors using random projection tree search.
sgdBatches | sgdBatches