This is an R Markdown web page presentation. In this web page, plotly package shall be used to display graphs in 3D.

iris dataset used for plotting

• predictors : Sepal Length, Sepal Width, Petal length, Petal Width

• Response : Species - factors of levels: setosa, versicol, virginica

library(caret)
library(plotly)
library(ggplot2)
library(dplyr)
summary(iris)
intrain <- createDataPartition(y=iris$Species, p = 0.70,list=FALSE)
training <- iris[intrain,]
testing <- iris[-intrain, ]

plot(x=iris$Sepal.Length, y=iris$Sepal.Width,  col=iris$Species)
modelfit <- train(Species~., data=iris, method="rf")
modelfit
predOut <- predict(modelfit, newdata=testing[, -5])
predOut
confusionMatrix(predOut, testing$Species)

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(ggplot2)

plot_ly(x=iris$Sepal.Length, y=iris$Sepal.Width, 
        z=iris$Petal.Length, color=as.factor(iris$Species), mode="markers",
        type="scatter3d", showlegend=TRUE)