Description Usage Arguments Value Examples
Visualize centroids produced by clustering function like k-means.
Plots available are line plot, bar plot, or heatmap. Parameter format
specifies which one to create.
1 2 3 4 5 6 7 8 | createCentroidPlot(km, format = "line", groupByCluster = TRUE,
clusters = rownames(km$centers), dims = colnames(km$centers),
baseSize = 12, baseFamily = "serif", title = paste("Cluster Centroids",
format, "Plot"), xlab, ylab = ifelse(format == "heatmap", "cluster",
ifelse(!is.null(km$scale) && km$scale, "scaled value", "value")),
legendPosition = ifelse(format == "bar", "none", "right"),
coordFlip = FALSE, ticks = FALSE, defaultTheme = theme_tufte(base_size =
baseSize, base_family = baseFamily, ticks = ticks), themeExtra = NULL)
|
km |
an object of class |
format |
type of plot to use: |
groupByCluster |
logical: indicates if centroids are grouped by clusters or variables. |
clusters |
optional vector with clusters to include. If vector has named values then names are used for cluster labels. By default, all clusters are included. |
dims |
optional vector with dimensions to include. Vector may be contain either dimension indices or names. By default, all dimensions are included. |
baseSize |
|
baseFamily |
|
title |
plot title. |
xlab |
a label for the x axis, defaults to a description of x. |
ylab |
a label for the y axis, defaults to a description of y. |
legendPosition |
the position of legends. ("left", "right", "bottom", "top", or two-element numeric vector). "none" is no legend. |
coordFlip |
logical flipped cartesian coordinates so that horizontal becomes vertical, and vertical horizontal (see coord_flip). |
ticks |
|
defaultTheme |
plot theme settings with default value |
themeExtra |
any additional |
ggplot object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | if(interactive()){
# initialize connection to Lahman baseball database in Aster
conn = odbcDriverConnect(connection="driver={Aster ODBC Driver};
server=<dbhost>;port=2406;database=<dbname>;uid=<user>;pwd=<pw>")
km = computeKmeans(conn, "batting", centers=5, iterMax = 25,
aggregates = c("COUNT(*) cnt", "AVG(g) avg_g", "AVG(r) avg_r", "AVG(h) avg_h"),
id="playerid || '-' || stint || '-' || teamid || '-' || yearid",
include=c('g','r','h'), scaledTableName='kmeans_test_scaled',
centroidTableName='kmeans_test_centroids',
where="yearid > 2000")
createCentroidPlot(km)
# As clusters fluctuate from run to run cluster names may be inconsistent
createCentroidPlot(km, format="bar_dodge",
clusters=c(Stars=3, Reserve=4), dims=c('g','h'))
createCentroidPlot(km, format="heatmap", coordFlip=TRUE)
}
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