PREDICTION ON THE IRIS DATA SET

IN this application they are two inputs which are “radio buttons” and “slider”.
The radio button are helping you to choose the “machine learning algorithm” and
slider helps you to choose the prediction data set size.

The prediction is done by three algorithms
=> random forest
=> multivarite regression
=> decision trees

these are done using caret .
there is correlated graph and “decision tree”
there is the plot which are differentiate with right and wrong prediction

the code for the model training

model <- train(Species~.,data=iris,method = "rf")
model <- train(Species~.,data=iris,method = "gbm")
model <- train(Species~.,data=iris,method = "rpart")

summary(cars)

     speed           dist       
 Min.   : 4.0   Min.   :  2.00  
 1st Qu.:12.0   1st Qu.: 26.00  
 Median :15.0   Median : 36.00  
 Mean   :15.4   Mean   : 42.98  
 3rd Qu.:19.0   3rd Qu.: 56.00  
 Max.   :25.0   Max.   :120.00