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We apply and compare a random Bayes forest classifier and three traditional classification methods to a dataset of complex benthic macroinvertebrate images of known taxonomical identity. Since in biomonitoring changes in benthic macroinvertebrate taxa proportions correspond to changes in water quality, their correct estimation is pivotal. As classification errors are passed on to the allocated proportions,...
Side effect machines operate by associating side effects with the states of a finite state machine. The use of side effect machines permits the researcher to leverage information stored in the state transition structure, making machines that might be identical as recognizers behave differently as classifiers. The side effect machines in this study associate a counter with each state so that the number...
The practical methodologies of stable pattern classification using artificial intelligence as advisory tools are researched here according to studies in the flowering plant genera Lithops N. E. Br. (Aizoaceae). In this paper, the use of a neural network model with the adaptive resonance theory is a practical generation of groups as a classifier for botanical taxa. In order to provide comparisons for...
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