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Definitions (43)
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resubstitution accuracy
The accuracy (error/loss) made by the model on the training data.
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utility
See Cost.
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tuple
See Feature vector.
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unsupervised learning
Learning techniques that group instances without a pre-specified dependent attribute. Clustering algorithms are usually unsupervised.
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specificity
True negative rate (see Confusion matrix).
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sensitivity
True positive rate (see Confusion matrix).
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record
see Feature vector.
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regressor
A mapping from unlabeled instances to a value within a predefined metric space (e.g., a continuous range).
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model deployment
The use of a learned model. Model deployment usually denotes applying the model to real data.
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model
A structure and corresponding interpretation that summarizes or partially summarizes a set of data, for description or prediction. Most inductive algorithms generate models that can then be used as cl [..]
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