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Toplam kayıt 6, listelenen: 1-6
Mapping classifiers and datasets
(Pergamon-Elsevier Science Ltd, 2011-04)
Given the posterior probability estimates of 14 classifiers on 38 datasets, we plot two-dimensional maps of classifiers and datasets using principal component analysis (PCA) and Isomap. The similarity between classifiers ...
Quadratic programming for class ordering in rule induction
(Elsevier Science BV, 2015-03-01)
Separate-and-conquer type rule induction algorithms such as Ripper, solve a K>2 class problem by converting it into a sequence of K - 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in ...
Tree Ensembles on the induced discrete space
(Institute of Electrical and Electronics Engineers Inc., 2016-05)
Decision trees are widely used predictive models in machine learning. Recently, K-tree is proposed, where the original discrete feature space is expanded by generating all orderings of values of k discrete attributes and ...
An adaptive locally connected neuron model: Focusing neuron
(Elsevier B.V., 2021-01-02)
This paper presents a new artificial neuron model capable of learning its receptive field in the topological domain of inputs. The experiments include tests of focusing neuron networks of one or two hidden layers on synthetic ...
Eigenclassifiers for combining correlated classifiers
(Elsevier Science Inc, 2012-03-15)
In practice, classifiers in an ensemble are not independent. This paper is the continuation of our previous work on ensemble subset selection [A. Ulas, M. Semerci, O.T. Yildiz, E. Alpaydin, Incremental construction of ...
Adaptive convolution kernel for artificial neural networks
(Academic Press Inc., 2021-02)
Many deep neural networks are built by using stacked convolutional layers of fixed and single size (often 3 × 3) kernels. This paper describes a method for learning the size of convolutional kernels to provide varying size ...