Journal ArticleDOI
A minimum entropy approach to rule learning from examples
Ioannis Pitas,E. Milios,Anastasios N. Venetsanopoulos +2 more
- Vol. 22, Iss: 4, pp 621-635
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TLDR
The system proposed is capable of obtaining the rules that fit a set of examples and counterexamples based on the minimal entropy (ME) criterion and can also set various parameters of the rule in such a way that entropy is minimized.Abstract:
Learning from examples uses specific instances (examples and counterexamples) to produce general rules. It is a convenient learning scheme in cases where the process of interviewing human experts and analyzing and formalizing their decision is very difficult or time consuming. The system proposed is capable of obtaining the rules that fit a set of examples and counterexamples based on the minimal entropy (ME) criterion. The system proposed can also set various parameters of the rule (e.g., thresholds) in such a way that entropy is minimized. The system can also handle incremental learning from examples. Applications of the proposed system to seismic image analysis are included. >read more
Citations
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Journal ArticleDOI
Three machine learning techniques for automatic determination of rules to control locomotion
TL;DR: The ability of generating rules for an FES controller was selected as the most important criterion when comparing the ML's and the minimal number of rules and the most explicit and comprehensible rules were obtained by ANFIS, and the best generalization was obtained by the IL and RBF network.
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User-expertise modeling with empirically derived probabilistic implication networks
TL;DR: A probabilistic user modeling approach, the POKS technique, which could serve as a standard user-expertise modeling tool and is successful in partially inferring an individual's knowledge state, either through the monitoring of a user's behavior, or through a selective questioning process.
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Sensor-driven four-channel stimulation of paretic leg: functional electrical walking therapy
Jovana Kojovic,Milica Djuric-Jovicic,Strahinja Dosen,Mirjana Popovic,Mirjana Popovic,Dejan B. Popovic,Dejan B. Popovic +6 more
TL;DR: The statistical strength of the clinical study was low, suggesting the need for a larger, randomized clinical trial, and significant differences in the mean values of all outcomes between the entry and end points of treatment were determined.
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A method of learning implication networks from empirical data: algorithm and Monte-Carlo simulation-based validation
Jiming Liu,Michel C. Desmarais +1 more
TL;DR: Comparisons consistently show that the results of predictions based on the induced networks would be comparable to those generated by Pearl's method, when reasoning in a variety of uncertain knowledge domains-those that were simulated using the presumed theoretical probabilistic networks of different topologies.
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Predicting quadriceps muscle activity during gait with an automatic rule determination method
Z.M. Nikolic,Dejan B. Popovic +1 more
TL;DR: An automatic method for obtaining the production rules from a set of examples is described, automatically induced from a model which used external sensor signals as inputs and electromyogram patterns as outputs, based on the minimization of entropy.
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