Results 251 to 260 of about 21,772 (300)

An explainable AI-driven hybrid feature selection approach for coronary artery disease diagnosis. [PDF]

Sci Rep
Elemam T, Refaat H, Makhlouf M.
europepmc   +1 more source

Computational models for the classification of antibody specificity using heavy chain features. [PDF]

PLoS One
Lin J, Chen J, Wan L, He W, Zhu Y, Qiao M, Meng F, Lin D, Che Y, Cao Z.   +9 more
europepmc   +1 more source

HANDLING AMBIGUOUS VALUES IN INSTANCE-BASED CLASSIFIERS

International Journal on Artificial Intelligence Tools, 2008
In an attempt to automate evaluation of network intrusion detection systems, we encountered the problem of ambiguously described learning examples. For instance, an attribute's value, or a class label, in a given example was known to be a or b but definitely not c or d.
Hans Holland, Miroslav Kubat, Jan Zizka
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Handling imbalance in hierarchical classification problems using local classifiers approaches

Data Mining and Knowledge Discovery, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rodolfo M Pereira, Yandre M G Costa, CARLOS N Silla   +2 more
exaly   +2 more sources

Handling Concept Drifts Using Dynamic Selection of Classifiers

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), 2016
This work describes the Dynse framework, which uses dynamic selection of classifiers to deal with concept drift. Basically, classifiers trained on new supervised batches available over time are add to a pool, from which is elected a custom ensemble for each test instance during the classification time.
Alceu De Souza Britto, Robert Sabourin
exaly   +2 more sources

Handling missing values in support vector machine classifiers

Neural Networks, 2005
This paper discusses the task of learning a classifier from observed data containing missing values amongst the inputs which are missing completely at random. A non-parametric perspective is adopted by defining a modified risk taking into account the uncertainty of the predicted outputs when missing values are involved.
Johan A K Suykens, Bart De Moor
exaly   +4 more sources

Occlusion Handling via Random Subspace Classifiers for Human Detection

IEEE Transactions on Cybernetics, 2014
This paper describes a general method to address partial occlusions for human detection in still images. The random subspace method (RSM) is chosen for building a classifier ensemble robust against partial occlusions. The component classifiers are chosen on the basis of their individual and combined performance.
David Vazquez, Antonio M Lopez, Jaume Amores   +2 more
exaly   +3 more sources

A method for Handling Inconsistencies in Rule-based Classifiers

IEEE Latin America Transactions, 2008
Researches on distributed data mining have as the main interest the development of algorithms and approaches that make possible the analysis of large and physically distributed datasets proposing better solutions in terms of costs and computational complexity.
Edson Emilio Scalabrin, Fabricio Enembreck   +1 more
exaly   +2 more sources