From the course: Data Science for Java Developers

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- [Instructor] Okay, for this demonstration, we're going to be using a different data set than the ones we've looked at before. Mainly, we're going to be using something called the Iris data set, which is an extremely popular, publicly available, data set that basically contains data about the measurements of different flowers. So, in other words, if you take a look at the iris.names file, you're going to see that there are three different species of flowers. And the data that's given to us for all of these flowers is the size in centimeters of different parts of the flower, right? Namely the sepal and the petals. So what we're going to do is we're going to build a classifier that based on the measurements of some new flower that we haven't yet classified, will predict which of the species that flower falls into. So, we're going to do this, first of all, with a K nearest neighbor classifier. But before we can actually start…

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