Results 231 to 240 of about 3,121,843 (279)

Bayesian classification and classification performance for independent distributions (Corresp.)

IEEE Transactions on Information Theory, 1981
Some general conditions are derived for the mean recognition accuracy of a Bayesian classifier to approach unity as the feature dimensionality increases to infinity.
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Classification Performance of Confidence-Driven Centroids

Cybernetics and Systems Analysis
Hyperdimensional computing (HDC) is a powerful algorithmic framework at the intersection of symbolic and neural network Artificial Intelligence. In particular, HDC has received significant attention as a suitable candidate for low-resource machine learning tasks, exemplified by wearable Internet of Things.
Smets, Laura, Rachkovskij, D., Osipov, E., Volkov, O., Van Leekwijck, W., Latré, Steven   +5 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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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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Cancer Literature Classification Methods Performance

2020 International Conference on Decision Aid Sciences and Application (DASA), 2020
The literary classification system is the best solution to improve the data search process. In terms of the need, its goal is to compare the relevant biomedical papers and discover novel knowledge to identify potential research issues. This paper will present cancer literature classification performance by comparing three approaches, Naive Bayes ...
Cheng-Yuan Ho, Mariana Syamsudin, Yueh-Chun Shen   +2 more
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Engineering classification for environmental performance

Geological Society, London, Engineering Geology Special Publications, 2001
The condition of natural soils and rocks reflects the impact of a historical sequence of geological processes (Fookes 1997), including plate tectonics, depositional environment, structural and diagenetic change. Climate influences the effect of the atmosphere in producing surface-related weathering and, in particular, the climatic changes of the ...
J. H. Charman, P. J. Carey, P. G. Fookes
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High Performance Packet Classification

2004
In this proposal, we seek to develop methods for packet classiï¬cation that can deliver high performance (e.g. wire speed processing at 10 Gb/s) while being reasonably cost-effective (e.g. memory-efficient and having low hardware complexity). In particular, we discuss a new approach involving extended TCAMs.
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Geomembranes: Classification, use and performance

Geotextiles and Geomembranes, 1984
Abstract The first applications of rubber-like and polymeric man-made materials, as linings of canals and reservoirs, were introduced about 40 years ago. Since then these materials have played an increasingly important role in modern civil engineering and especially in water conservation, agriculture and industrial water pollution control.
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Misregistration Effects On Classification Performance

SPIE Proceedings, 1987
An analytical investigation is described which relates errors in spatial registration of multispectral and multitemporal data sets to error in classification. Of particular interest is the classification of large areas of crops. Misregis-tration effects on the statistics of field-center and boundary pixels are studied.
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Measuring Performance in Classification Models

2013
When predicting a categorical outcome, some measure of classification accuracy is typically used to evaluate the model’s effectiveness. However, there are different ways to measure classification accuracy, depending of the modeler’s primary objectives. Most classification models can produce both a continuous and categorical prediction output.
Max Kuhn, Kjell Johnson
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