Machine Learning in R: k-means Clustering on Iris Dataset

The k-means algorithm is a Machine Learning technique that falls under the Unsupervised Learning category. The essence of the K means algorithm is that it is left to itself to find interesting patterns in a given dataset. In this project, we will use the k-means algorithm to group the data from the popular Iris Dataset into a few clusters.

Available On Coursera
Machine Learning in R: k-means Clustering on Iris Dataset

Duration (mins)


5.0 / 5


Task List

We will cover the following tasks in 26 minutes:


In this task, I will discuss the goal of the course, which is to use the k-means clustering algorithm to properly group three species of flowers given only the Petal Length and Petal Width. I will also discuss the dataset. We will go over the Rhyme Interface and I will turn on my Webcam and give you a short bio about me!

Exploratory Analysis

I suggest always doing some exploratory analysis on a dataset before embarking on any project. I will show you a few ways to go about exploratory analysis in this task. We will use the str() call, summary() call, and then use ggplot to graphically look at the data. Of course, there are many more techniques and depending on the project you may use these techniques or other techniques.


You can always look up the formula calls in the Help section by putting a question mark before the function. We will do that in this section with the k-means function. We will be using the dataframe, three centers and 20 nstarts. We can further explore the meaning of various arguments that we provide to the algorithm. We will also run the algorithm and store the trained k-means model in an object.

k-means Grouping (Graphically)

To see how the algorithm grouped the data graphically we need to first convert the clustered object into a factor. Then, it’s as easy as using ggplot on the original data and adding the cluster factors. I will show you how this is done in this task.


When looking at the accuracy visually we can usually do a decent job. However, if we need hard facts and hard data we will need to go a little further. This can be done using the table function. I will show you how to find out exactly how the algorithm performed using this function.

Watch Preview

Preview the instructions that you will follow along in a hands-on session in your browser.

Rhyme Authors

About the Host

Rhyme Authors

Frequently Asked Questions

In Rhyme, all projects are completely hands-on. You don't just passively watch someone else. You use the software directly while following the host's (Rhyme Authors) instructions. Using the software is the only way to achieve mastery. With the "Live Guide" option, you can ask for help and get immediate response.
Nothing! Just join through your web browser. Your host (Rhyme Authors) has already installed all required software and configured all data.
You can go to, sign up for free, and follow this visual guide How to use Rhyme to create your own projects. If you have custom needs or company-specific environment, please email us at
Absolutely. We offer Rhyme for workgroups as well larger departments and companies. Universities, academies, and bootcamps can also buy Rhyme for their settings. You can select projects and trainings that are mission critical for you and, as well, author your own that reflect your own needs and tech environments. Please email us at
Rhyme strives to ensure that visual instructions are helpful for reading impairments. The Rhyme interface has features like resolution and zoom that will be helpful for visual impairments. And, we are currently developing a close-caption functionality to help with hearing impairments. Most of the accessibility options of the cloud desktop's operating system or the specific application can also be used in Rhyme. If you have questions related to accessibility, please email us at
We started with windows and linux cloud desktops because they have the most flexibility in teaching any software (desktop or web). However, web applications like Salesforce can run directly through a virtual browser. And, others like Jupyter and RStudio can run on containers and be accessed by virtual browsers. We are currently working on such features where such web applications won't need to run through cloud desktops. But, the rest of the Rhyme learning, authoring, and monitoring interfaces will remain the same.
Please email us at and we'll respond to you within one business day.

No sessions available