C4.5: programs for machine learning
C4.5: programs for machine learning
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Computer-based system for training and ranking mobot operators-selection procedure
Annales UMCS, Informatica
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
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A description which summarizes entire and usually big set of data is called its model. The problem investigated in the paper consists in verification of models of data coming from a simulation experiment of selecting candidates for operators of mobile robot (more strictly building reliable predictive model of the data). The models are validated using train-and-test method and verified with the help of the EM (expectation-maximization) algorithm which was originally designed for solving clustering problems with missing data. Actually, the selecting is a clustering problem because the candidates are assigned to 'chosen', 'accepted' or 'rejected' subgroups. For such a case the missing data is the category (the subgroup) for which a candidate should be assigned on the basis of his activity measured during the simulation experiment. The paper explains the procedure of model verification. It also shows experimental results and draws conclusions.