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What is the difference between Supervised and unsupervised methods in data mining?
Wiki User
∙ 11y ago
Unsupervised Learning
• The model is not provided with the correct results
during the training.
• Can be used to cluster the input data in classes on
the basis of their statistical properties only.
• Cluster significance and labeling.
• The labeling can be carried out even if the labels are
only available for a small number of objects
representative of the desired classes.
Supervised Learning
• Training data includes both the input and the
desired results.
• For some examples the correct results (targets) are
known and are given in input to the model during
the learning process.
• The construction of a proper training, validation and
test set (Bok) is crucial.
• These methods are usually fast and accurate.
• Have to be able to generalize: give the correct
results when new data are given in input without
knowing a priori the target.
Wiki User
∙ 11y ago
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