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Abstract

The transductive confidence machine consists of data labelling apparatus which is capable of identifying for an unknown example, a range of most suitable labels from an infinite number of potential labels. The method identifies a range of possible label sets having a strangeness value below a certain pre-determined strangeness threshold, without pre-calculating the strangeness value of all of the possible label sets. The label sets each comprise training labelled examples and at least one unlabelled example, in each of the label sets each unlabelled example being associated with a different one of an infinite number of potential labels. The apparatus and method enable a mode of inference known as transductive inference, in which the labelling of every new unlabelled example is done independently. In general, no computations carried out in relation to other unlabelled examples can be re-used when a different unlabelled example is to be assigned a range of labels which are members of label sets having a strangeness value below the threshold strangeness value.

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First Claim