An ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of internet of things
N Moustafa, B Turnbull… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
Internet of Things (IoT) plays an increasingly significant role in our daily activities,
connecting physical objects around us into digital services. In other words, IoT is the driving …
connecting physical objects around us into digital services. In other words, IoT is the driving …
Research and development of neural network ensembles: a survey
H Li, X Wang, S Ding - Artificial Intelligence Review, 2018 - Springer
Abstract A Neural Network Ensemble (NNE) combines the outputs of several individually
trained neural networks in order to improve generalization performance. This article …
trained neural networks in order to improve generalization performance. This article …
Optimized classification predictions with a new index combining machine learning algorithms
A Tamvakis, CN Anagnostopoulos… - … Journal on Artificial …, 2018 - World Scientific
Voting is a commonly used ensemble method aiming to optimize classification predictions
by combining results from individual base classifiers. However, the selection of appropriate …
by combining results from individual base classifiers. However, the selection of appropriate …
Integration base classifiers in geometry space by harmonic mean
R Burduk - Artificial Intelligence and Soft Computing: 17th …, 2018 - Springer
One of the most important steps in the formation of multiple classifier systems is the fusion
process. The fusion process may be applied either to class labels or confidence levels …
process. The fusion process may be applied either to class labels or confidence levels …
The use of geometric mean in the process of integration of three base classifiers
R Burduk, A Kasprzak - … 2018, Olomouc, Czech Republic, September 27 …, 2018 - Springer
One of the most important steps in the formation of multiple classifier systems is the
integration process also called the base classifiers fusion. The fusion process may be …
integration process also called the base classifiers fusion. The fusion process may be …
High-dimensional and one-class classification
F Fortunato - 2018 - amsdottorato.unibo.it
When dealing with high-dimensional data and, in particular, when the number of attributes p
is large comparatively to the sample size n, several classification methods cannot be …
is large comparatively to the sample size n, several classification methods cannot be …
Recursive harmony search based classifier Ensemble reduction
P Kailas, K Chandrasekaran - 2018 Second International …, 2018 - ieeexplore.ieee.org
In recent times classifier ensembles have become a mainstay in data mining and machine
learning. The combination of several classifiers generally results in better performance and …
learning. The combination of several classifiers generally results in better performance and …
Filter Training and Maximum Response: Classification via Discerning
L Gu - 2018 - openreview.net
This report introduces a training and recognition scheme, in which classification is realized
via class-wise discerning. Trained with datasets whose labels are randomly shuffled except …
via class-wise discerning. Trained with datasets whose labels are randomly shuffled except …