… (CNN), and whose complexity depends on the size of the convolutional filter and … rule
extraction from binary neural networks with stochastic local search. We show how to extract rules …

… Experiments based on cross-validation emphasize that our … cross-validation with many more
examples of extracted rules. … above to a well-known binary classification problem related to “…

… a binary rule from a neural network which is trained with binary input. … extracting
understandable rules. Consequently, we can use DNN for different problem domains where …

… So even use evaluation methods such as cross validation, it … a wide variety of rule extraction
algorithms, the major … is generated by a trained convolutional neural network(CNN). This …

… of convolutional neural networks(CNNs). We propose to generate propositional rules from
CNNs, … is that we can run in parallel all rule extractions for new binary classification problems. …

… from the relevant protective laws and regulations and therefore … , bank of Gabor filters, local
binary pattern, bag of features and … Accuracy of model on training and validation set tells us …

… This domainspeci c legality checking would vary for di erent … We use Drebin [5, 62] to extract
a total of 545,333 binary features … with deep convolutional neural networks. In Advances in …

… to the slow checkers and rules complexity. Machine learning … This work uses a convolutional
neural network (CNN) to predict … This work results in a binary classifier to identify layouts …

… and Rule Extraction (DEXiRE). Such a tool approximates … rule length in the rule set per
fold in five-fold cross-validation. … with convolutional neural networks (CNN), recurrent neural …

… of classification models, we can find that the binary models … in Convolutional Neural Networks,
are highly explainable by … ) on basis of 10-fold cross-validation where we get 10 results …