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011 0/1 point (graded) Now we will perform some exploratory data analysis on the data. plot(iris,pch=21,bg=iris$3pecies) I Notice that Petal.Length and Petal.width in combination could

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011 0/1 point (graded) Now we will perform some exploratory data analysis on the data. plot(iris,pch=21,bg=iris$3pecies) I Notice that Petal.Length and Petal.width in combination could potentially be more information than either feature alone. Optimize the the cutoffs for Petal. Length and PetalMidth separately in the train dataset by using the seqfunction with increments of 0.1. Then, report the overall accuracy when applied to the test dataset by creating a rule that predicts virginica if Petal.Length is greater than the length cutoff OR Petal.width is greater than the width cutoff, and versicolor otherwise. What is the overall accuracy for the test data now? incorrect .92

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