Publication | Closed Access
On the Problem of Bias in Multinomial Classification
21
Citations
10
References
1977
Year
Classification MethodEngineeringMachine LearningExact BiasData MiningAutomatic ClassificationBiasStatistical FoundationKnowledge DiscoveryMultinomial ClassificationIntelligent ClassificationStatistical InferenceState ProbabilitiesLikelihood Ratio RuleMathematical StatisticDecision ScienceStatistics
Summary Assuming sampling from two multinomial distributions and the use of a sample based likelihood ratio rule as ani optimiial classification procedure, ani algebraic expression is derived jor the exact bias of'the apparenit error rate. Properties that govern the behavior oJ'the bias are discussed and comparisons to a bound by Glick (1973) are miiade. Tables are genierated givinig exact state bias jor various combinations of state probabilities and samiiple sizes. Suggestions are provided j6or proceeding in practical situations.
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