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@nwstephens
Created October 11, 2016 20:57
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---
title: "Iris K-Means Clustering"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
runtime: shiny
---
```{r global, include=FALSE}
# load data in 'global' chunk so it can be shared by all users of the dashboard
library(datasets)
data(iris)
```
Column {.sidebar}
-----------------------------------------------------------------------
```{r}
selectInput('xcol', 'X Variable', names(iris))
selectInput('ycol', 'Y Variable', names(iris),
selected=names(iris)[[2]])
numericInput('clusters', 'Cluster count', 3,
min = 1, max = 9)
```
Column
-----------------------------------------------------------------------
### K Means
```{r}
palette(c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
"#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999"))
# Combine the selected variables into a new data frame
selectedData <- reactive({
iris[, c(input$xcol, input$ycol)]
})
clusters <- reactive({
kmeans(selectedData(), input$clusters)
})
renderPlot({
par(mar = c(5.1, 4.1, 0, 1))
plot(selectedData(),
col = clusters()$cluster,
pch = 20, cex = 3)
points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
})
session$allowReconnect("force")
```
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