| plot_kmeans {modeldb} | R Documentation |
Visualize a KMeans Cluster with lots of data
Description
It uses 'ggplot2' to display the results of a KMeans routine. Instead of a scatterplot, it uses a square grid that displays the concentration of intersections per square. The number of squares in the grid can be customized for more or less fine grain.
Usage
plot_kmeans(df, x, y, resolution = 50, group = center)
db_calculate_squares(df, x, y, group, resolution = 50)
Arguments
df |
A Local or remote data frame with results of KMeans clustering |
x |
A numeric variable for the x axis |
y |
A numeric variable for the y axis |
resolution |
The number of squares in the grid. Defaults to 50. Meaning a 50 x 50 grid. |
group |
A discrete variable containing the grouping for the KMeans. It defaults to 'center' |
Details
For large result-sets in remote sources, downloading every intersection will be a long running, costly operation. The approach of this function is to devide the x and y plane in a grid and have the remote source figure the total number of intersections, returned as a single number. This reduces the granularity of the visualization, but it speeds up the results.
Examples
plot_kmeans(mtcars, mpg, wt, group = am)