KMeans Clustering for IRIS Dataset Classification
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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
