Machine Learning: Supervised versus Unsupervised - what's the difference?
Unsupervised learning is an algorithmic way to implement "birds of a feather flock together."
To do supervised learning, you supply the right answers. Not so with unsupervised learning...
Learn more:
Supervised - http://bit.ly/quaesita_supervised
Unsupervised - http://bit.ly/quaesita_unsupervised
Apophenia - http://bit.ly/quaesita_inkblot
Note: Although some folks insist on making semantic distinctions between clustering and other breeds of unsupervised learning, they all use similarity to shuffle your data. For example, anomaly detection methods reveal outliers by asking, "What's left over when the similar things have been grouped?" After all, to reveal the dissimilar, you must first group the similar.
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