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The Inductive Confidence Machine (ICM) provides an alternative method to that of the Transductive Confidence Machine (TCM) for complementing the bare predictions produced by traditional machine-learning algorithms with measures of confidence. These measures give an indication of how 'good' each prediction is, which is highly desirable in risk-sensitive applications. The motivation behind the introduction of the ICM was to produce algorithms that overcome the computational inefficiency problemsdoi:10.1017/s0269888909990233 fatcat:mrer7ktwa5fpljfxuv5hyarmxy