DUE DATE: 11/10/20
• Read and store the attached iris data (iris.csv) using a process
• Start a new process and do the following
• Retrieve the stored data using a Retrieve operator
• You are required to build a decision tree model for predicting the species of iris flower(species) using the rest of the columns in the dataset as predictors.
• Since you want to predict species, use the Set Role operator to set the species column as label
• Now split the data with 75% in training and 25% in test using the Split Data operator
• Now use the Decision Tree operator to build the model on the training dataset
• Now use the Apply Model operator and create the predictions. Make sure you input the test part of the dataset from the split data operator.
• Now use the performance operator to compute the confusion matrix and accuracy of the tree model
• Output the tree diagram (the model) to the results
• Turn in the RapidMiner file (.rmp)
• NOTE: Watching this video will help with this homework
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