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The Artificial intelligence review, ISSN 1573-7462, 2009, Volume 33, Issue 1-2, pp. 1 - 39
...Artif Intell Rev (2010) 33:1–39 DOI 10.1007/s10462-009-9124-7 Ensemble-based classifiers Lior Rokach Published online: 19 November 2009 © Springer Science... 
Supervised learning | Computer Science | Classification | Artificial Intelligence (incl. Robotics) | Ensemble of classifiers | Boosting | Computer Science, general | NEURAL NETWORKS | ALGORITHM | DECOMPOSITION | EXPERTS | RANDOM SUBSPACE METHOD | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ACCURACY | MULTIPLE CLASSIFIERS | DECISION TREES | DIVERSITY
Journal Article
Pattern Recognition, ISSN 0031-3203, 12/2018, Volume 84, pp. 82 - 96
.... This work proposes a new type of classifier called Morphological Classifier (MC). MCs aggregate concepts from mathematical morphology and supervised learning... 
Morphological classifier | Set theory | Supervised learning | Mathematical morphology | IMAGE | SEGMENTATION | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer science | Analysis
Journal Article
IEEE transactions on evolutionary computation, ISSN 1941-0026, 2019, Volume 23, Issue 5, pp. 885 - 898
Journal Article
ACM Computing Surveys (CSUR), ISSN 0360-0300, 07/2014, Volume 47, Issue 1, pp. 1 - 43
Journal Article
Pattern recognition, ISSN 0031-3203, 2016, Volume 55, pp. 247 - 260
Journal Article
IEEE/ACM transactions on networking, ISSN 1558-2566, 2010, Volume 18, Issue 5, pp. 1505 - 1515
Journal Article
IEEE transactions on image processing, ISSN 1941-0042, 2018, Volume 27, Issue 12, pp. 6064 - 6078
.... First, the probabilistic contribution of each image region to the confidence of a convolutional neural network-based image classifier is computed through a backtracking strategy to produce TD saliency... 
Visualization | Cats | semantic segmentation | Task analysis | Top-down saliency | Training | weakly supervised training | Semantics | object localization | Object detection | Feature extraction | CNN image classifier | salient object detection | object detection | DEEP | VISUAL SALIENCY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer Science - Computer Vision and Pattern Recognition
Journal Article
Knowledge-based systems, ISSN 0950-7051, 2011, Volume 24, Issue 6, pp. 775 - 784
.... One of the simplest methods, the naive Bayes classifier, has often been found to give good performance despite the fact that its underlying assumptions... 
Logistic regression | UCI data sets | Breast cancer | Naive Bayes | Supervised learning | SURVIVAL | GENE-EXPRESSION SIGNATURE | INCOMPLETE DATA | HUMAN BREAST-TUMORS | CANCER | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Neurocomputing, ISSN 0925-2312, 09/2016, Volume 207, pp. 141 - 149
.... Therefore, dealing with directional data requires special methods. So far, the design of classifiers for periodic variables adopts a generative approach based on the usage of the von Mises distribution or variants... 
Logistic regression | Directional statistics | Supervised classification | Discriminative models | REGRESSION | DISTRIBUTIONS | MIXTURES | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
International Journal of Approximate Reasoning, ISSN 0888-613X, 2009, Volume 50, Issue 2, pp. 341 - 362
When learning Bayesian network based classifiers continuous variables are usually handled by discretization, or assumed that they follow a Gaussian distribution... 
Kernel density estimation | Bayesian network | Supervised classification | Flexible naive Bayes | BIAS | CLASSIFICATION | NETWORKS | VARIANCE | EQUIVALENCE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Artificial intelligence
Journal Article
ACM Transactions on Knowledge Discovery from Data (TKDD), ISSN 1556-4681, 08/2019, Volume 13, Issue 4, pp. 1 - 10
Journal Article