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K Means clustering is an unsupervised machine learning algorithm. An example of a supervised learning algorithm can be seen when looking at Neural Networks where the learning process involved both the inputs (x) and the outputs (y). During the learning process the error between the predicted outcome and actual outcome (y) is used to train the system. In an unsupervised method such as K Means clustering the outcome (y) variable is not used in the training process.
In this example we look at using the IRIS dataset and cover:
Importing the sample IRIS dataset Converting the dataset to a Pandas Dataframe Visualising the classifications using scatter plots Simple performance metrics
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