Visualising How Nonlinear Dimension Reduction Warps Your Data
Assign data to hexagons
Augment Data with Predictions and Error Metrics for NLDR Models
S3 generic for augment
Create a tibble with averaged high-dimensional data
Calculate 2-D Euclidean distances between vertices
Calculate the effective number of bins along x-axis and y-axis
Create a tibble with averaged high-dimensional data and high-dimension...
Create a tibble with averaged high-dimensional data and high-dimension...
Create a tibble with averaged high-dimensional data and high-dimension...
Compute mean density of hexagonal bins
Compute standardise counts in hexagons
Find low-density Hexagons
Find the number of bins required to achieve required number of non-emp...
Construct the 2-D model and lift into high-dimensions
Generate Axes for Projection
Generate centroid coordinate
Generate a design to layout 2-D representations
Generate erros and MSE for different bin widths
Generate edge information
Generate hexagonal polygon coordinates
Scaling the NLDR data
Create a hexgrid plot
Create a trimesh plot
GeomHexgrid: A Custom ggplot2 Geom for Hexagonal Grid
GeomTrimesh: A Custom ggplot2 Geom for Triangular Meshes
Compute Projection for High-Dimensional Data
Generate evaluation metrics for a hex_model object
S3 generic for glance
Grouped points in each hexagon
Hexagonal binning
Extract hexagonal bin centroids coordinates and the corresponding stan...
Extract hexagonal bin mean coordinates and the corresponding standardi...
Plot Projected Data with Axes and Circles
Arrange RMSE plot and 2-D layouts
Predict 2-D embeddings
Solve Quadratic Equation for Positive Real Roots
Visualise the model overlaid on high-dimensional data along with 2-D w...
Visualise the model overlaid on high-dimensional data
Visualise the model overlaid on high-dimensional data along with 2-D w...
stat_hexgrid Custom Stat for hexagonal grid plot
stat_trimesh Custom Stat for trimesh plot
Triangulate bin centroids
Update from and to values in trimesh data
To construct a model in 2-D space from 2-D nonlinear dimension reduction data and then lift it to the high-dimensional space. Additionally, provides tools to visualise the model overlay the data in 2-D and high-dimensional space. Furthermore, provides summaries and diagnostics to evaluate the nonlinear dimension reduction layout.
Useful links