Results 221 to 230 of about 819,529 (261)

Performance Prediction for Classification Systems

1999
Performance prediction for classification systems is important. We present new techniques for such predictions in settings where data items are to be classified into two categories. Our results can be integrated into existing classification systems and provide an accurate and predictable tool for data mining.
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On the performance of the HONG network for pattern classification

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
A neural network model called the hierarchical overlapped neural gas (HONG) network is introduced and its performance on several datasets is described. In order to obtain improved classification accuracy, the HONG network partitions the input space by projecting the input data onto several different second layer neural gas networks.
Ajantha S. Atukorale, Tom Downs, Ponnuthurai N. Suganthan   +2 more
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Classification of cognitive performance in bipolar disorder

Cognitive Neuropsychiatry, 2017
To understand the etiology of cognitive impairment associated with bipolar disorder, we need to clarify potential heterogeneity in cognitive functioning. To this end, we used multivariate techniques to study if the correlation structure of cognitive abilities differs between persons with bipolar disorder and controls.Clinically stable patients with ...
Timea Sparding, Katja Silander, Erik Pålsson, Josefin Östlind, Carl Johan Ekman, Carl M. Sellgren, Erik Joas, Stefan Hansen, Mikael Landén   +8 more
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The performance of classification criteria for juvenile spondyloarthropathies

Rheumatology International, 2017
Juvenile spondyloarthropathies (JSpA) are a group of rheumatologic diseases with a disease onset before 16; characterized with enthesitis, lower extremity oligoarthritis, involvement of the axial skeleton and HLA B27 positivity. The diversity of classification criteria along with the phenotype heterogeneity makes the classification of JSpA challenging.
Amra Adrovic, Metin Sezen, Kenan Barut, Sezgin Sahin, Cengizhan Acikel, Erkan Demirkaya, Ozgur Kasapcopur   +6 more
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Performance Analysis of Modulation Classification with a Preprocessing

2020 International Conference on Information and Communication Technology Convergence (ICTC), 2020
In this paper, we propose a preprocessing method for automatic modulation classification that allows reliable classification of the digital baseband modulation schemes whose signal constellations have symmetry about the in-phase and quadrature axes. The proposed preprocessing is used to generate additional data for modulation classification based on ...
Seongjin Ahn, Dongweon Yoon, Hongsuk Shim, Sungkyun Park   +3 more
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Performance Evaluation of Face Classification Systems

2015
In this paper face classification systems based on 3D images are compared in terms of classification and metrological performance in presence of image uncertainty. In previous papers the authors proposed a new approach to classification and recognition problems.
Betta, Giovanni, CAPRIGLIONE, Domenico, Corvino, Mariella, Gasparetto, Michele, LIGUORI, CONSOLATINA, PAOLILLO, Alfredo, Zappa, Emanuele   +6 more
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A hybrid approach for improving the classification performance

2017 International Conference on Computer Science and Engineering (UBMK), 2017
There are many factors that affect the performance of classification. The volume, size, type of data and classification methods are the most obvious factors. For the exact same data set, it is possible to achieve different classification performance values by using different classification methods Hence, the development of classification models that ...
Davarci, Murat Emre, KÖK, İBRAHİM, Ozdemir, Suat   +2 more
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Evaluating the Performance of Classification Algorithms for Land-Cover Classification

2023 International Conference on Machine Learning and Applications (ICMLA), 2023
Marcos Pastorini, Angela Gorgoglione, Rafael Rodríguez, Lorena Etcheverry, Alberto Castro   +4 more
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Classification Performance Evaluation

2011
A great part of this book presented the fundamentals of the classification process, a crucial field in data mining. It is now the time to deal with certain aspects of the way in which we can evaluate the performance of different classification (and decision) models. The problem of comparing classifiers is not at all an easy task.
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Improving classification performance using metaclasses

SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2004
In this paper we propose a new methodology to improve the performance of classifiers on relatively difficult classification problems with complex boundaries between classes, overlapping classes, and a lack of sufficient number of samples for some classes. We investigate the use of contextual information to overcome such problems, especially in the case
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