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In order to obtain the minimum error, the deep network parameters will be updated based on learning rules.
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In this paper, we propose a new heuristic algorithm, where the criterion is based on min max learning rule and fuzzy extension matrix is designed as the search strategy.
Results of the experiments justify that the new method outperforms similar ones because of employing knowledge sharing technique, reasonable exploration logic, and learning rules based on the action trajectory.
As update directions (8) descend the gradient of an infinitely differentiable convex function, learning rules based on them have good convergence rates [23].
controlled performance based on formal rule learning; automatic performance in a test situation; controlled performance based on implicit (unconscious) learning.
Unsupervised learning rules update the connectivity exclusively based on the value of the activity variable.
We employed machine learning techniques based on the rules developed from this study to examine the proteins that have crystallographic structure information available at NGS.
Artificial neural networks (ANNs), mathematical models that mimic BNNs, are typically built as structured node groups with activation functions and connection weights that are adjusted based on the applied learning rules (Hampson, 1991, 1994; Basheer and Hajmeer, 2000; Krogh, 2008).
The approach was based on both rules and machine learning techniques.
Using machine learning methods based on these rules we can predict with 93% accuracy if a particular site will be glycosylated.
The method is based on the iterative rule learning approach to fuzzy rule base system design.
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