plot_kmeans: Visualize a KMeans Cluster with lots of data

In edgararuiz/modeldb: Fits Models Inside the Database

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)

edgararuiz/modeldb documentation built on Jan. 18, 2024, 4:53 a.m.