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Relevant bibliographies by topics / Classification correctness

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Academic literature on the topic 'Classification correctness'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Classification correctness"

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Yaroshynskyi, M. S., O. V. Sirotkin, D. P. Sinko, S. B. Hunko, and D. O. Manoliuk. "Correctness of Flat Classification." Èlektronnoe modelirovanie 45, no. 2 (2023): 34–43. http://dx.doi.org/10.15407/emodel.45.02.034.

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Classifications are widely used in semantic networks and decision support systems based on formal knowledge and are part of computer ontologies. Classifications and computer ontologies built on them are the result of the work of one or more experts. As a result, such classifications reflect the subjective view of the author or authors on the world and the relationship between the classes (concepts) of the created classification. In the work, the authors propose an approach that will allow assessing how correctly the classification is constructed.

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KRAVTSOV, H. A., and V. I. KOSHEL. "Classification Calculus. The Classification Correctness." Èlektronnoe modelirovanie 39, no. 5 (2017): 59–70. http://dx.doi.org/10.15407/emodel.39.05.059.

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Kopp, Andrii, Dmytro Orlovskyi, and Uliya Litvinova. "DEVELOPMENT AND RESEARCH OF SOFTWARE SOLUTION FOR BUSINESS PROCESS MODEL CORRECTNESS ANALYSIS USING MACHINE LEARNING." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 1 (11) (July 30, 2024): 39–46. http://dx.doi.org/10.20998/2079-0023.2024.01.06.

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Poorly designed business process models are a source of errors and the subsequent costs associated with these errors, such as monetary costs, lost time, or even some harmful impact on people or the environment if the erroneous business process models are associated with critical industries. The BPM (Business Process Management) lifecycle usually consists of designing, implementing, monitoring, and controlling the business process execution, but it lacks continuous quality control of the created BPMN (Business Process Model and Notation) models. Thus, this paper considers the problem of busines

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Matsumoto, Kazuma, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, and Keiki Takadama. "XCSR Learning from Compressed Data Acquired by Deep Neural Network." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 5 (2017): 856–67. http://dx.doi.org/10.20965/jaciii.2017.p0856.

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The correctness rate of classification of neural networks is improved by deep learning, which is machine learning of neural networks, and its accuracy is higher than the human brain in some fields. This paper proposes the hybrid system of the neural network and the Learning Classifier System (LCS). LCS is evolutionary rule-based machine learning using reinforcement learning. To increase the correctness rate of classification, we combine the neural network and the LCS. This paper conducted benchmark experiments to verify the proposed system. The experiment revealed that: 1) the correctness rate

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Pelánek, Radek, and Tomáš Effenberger. "Beyond binary correctness: Classification of students’ answers in learning systems." User Modeling and User-Adapted Interaction 30, no. 5 (2020): 867–93. http://dx.doi.org/10.1007/s11257-020-09265-5.

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Mrowicka, Blanka, Magdalena Kosińska, and Szczepan Cofta. "Morphological classification of patients with sleep obstructive disturbances." Anthropological Review 66 (June 30, 2003): 87–93. http://dx.doi.org/10.18778/1898-6773.66.07.

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It has been suggested that enlarged values of morphological measurements manifesting obesity intensify the risk of sleep disturbances. The main goal of this work was to find a set of predictor morphometric variables that best distinguish between the mutually exclusive groups of interest, the well and the ill – i.e., those who suffer from obstructive sleep apnoea (OSA) syndrome, and healthy patients. Somatic measurements of 96 males were taken. To analyze the dependencies between the degree of intensity of the studied pathology (oxygen desaturation index) and the values of the somatic measureme

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Zahoor, Kanwal, Narmeen Zakaria Bawany, and Tehreem Qamar. "Evaluating text classification with explainable artificial intelligence." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 278. http://dx.doi.org/10.11591/ijai.v13.i1.pp278-286.

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<span lang="EN-US">Nowadays, artificial intelligence (AI) in general and machine learning techniques in particular has been widely employed in automated systems. Increasing complexity of these machine learning based systems have consequently given rise to blackbox models that are typically not understandable or explainable by humans. There is a need to understand the logic and reason behind these automated decision-making black box models as they are involved in our day-to-day activities such as driving, facial recognition identity systems, online recruitment. Explainable artificial inte

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Zahoor, Kanwal, Narmeen Zakaria Bawany, and Tehreem Qamar. "Evaluating text classification with explainable artificial intelligence." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 278–86. https://doi.org/10.11591/ijai.v13.i1.pp278-286.

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Nowadays, artificial intelligence (AI) in general and machine learning techniques in particular has been widely employed in automated systems. Increasing complexity of these machine learning based systems have consequently given rise to blackbox models that are typically not understandable or explainable by humans. There is a need to understand the logic and reason behind these automated decision-making black box models as they are involved in our day-to-day activities such as driving, facial recognition identity systems, online recruitment. Explainable artificial intelligence (XAI) is an evol

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Ruah, Carlos B., David Cohen, and Jacob Sadé. "Eustachian tube teratoma and its terminological correctness." Journal of Laryngology & Otology 113, no. 3 (1999): 271–74. http://dx.doi.org/10.1017/s0022215100143774.

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AbstractTeratomas are germ cell tumours usually found in the young and are characteristically composed of tissue foreign to the place where they arise. Two teratomas of the middle ear were first described in 1866 and since then, and to the best of our knowledge, 19 additional cases have been reported in the literature under different terms such as hairy congenital polyps, epidermoid cysts, dermoid cysts, hamartoma, cutaneous teratoma and teratomas. The difficulty in classifying germ cell tumours may explain the different terminologies encountered in the literature. The authors describe a case

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Tran, G., D. Nguyen, M. Milenkovic, and N. Pfeifer. "POTENTIAL OF FULL WAVEFORM AIRBORNE LASER SCANNING DATA FOR URBAN AREA CLASSIFICATION – TRANSFER OF CLASSIFICATION APPROACHES BETWEEN MISSIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 30, 2015): 1317–23. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-1317-2015.

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Full-waveform (FWF) LiDAR (Light Detection and Ranging) systems have their advantage in recording the entire backscattered signal of each emitted laser pulse compared to conventional airborne discrete-return laser scanner systems. The FWF systems can provide point clouds which contain extra attributes like amplitude and echo width, etc. In this study, a FWF data collected in 2010 for Eisenstadt, a city in the eastern part of Austria was used to classify four main classes: buildings, trees, waterbody and ground by employing a decision tree. Point density, echo ratio, echo width, normalised digi

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Dissertations / Theses on the topic "Classification correctness"

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Behrens, Diogo, Marco Serafini, Sergei Arnautov, Flavio Junqueira, and Christof Fetzer. "Scalable error isolation for distributed systems: modeling, correctness proofs, and additional experiments." Technische Universität Dresden, 2015. https://tud.qucosa.de/id/qucosa%3A29539.

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Do, Dang-Khoa. "Zuverlässige numerische Berechnungen mit dem Spigot-Ansatz." Doctoral thesis, Technische Universität Dresden, 2004. https://tud.qucosa.de/id/qucosa%3A24875.

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Der Spigot-Ansatz ist eine elegante Vorgehensweise, spezielle numerische Werte zuverlässig, effizient und mit beliebiger Genauigkeit zu berechnen. Die Stärke des Ansatzes ist seine Effizienz, seine totale Korrektheit und seine mathematisch exakt begründete Sicherstellung einer gewünschten absoluten Genauigkeit. Seine Schwäche ist möglicherweise die eingeschränkte Anwendbarkeit. Es gibt in der Literatur Spigot-Berechnung für e und pi. Wurzelberechnung und Logarithmenberechnung gehören zu den Hauptergebnissen der Dissertation. In Kombination mit den Methoden der Reihentransformation von Zeilberg

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Hilbrich, Tobias. "Runtime MPI Correctness Checking with a Scalable Tools Infrastructure." Doctoral thesis, 2014. https://tud.qucosa.de/id/qucosa%3A28832.

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Increasing computational demand of simulations motivates the use of parallel computing systems. At the same time, this parallelism poses challenges to application developers. The Message Passing Interface (MPI) is a de-facto standard for distributed memory programming in high performance computing. However, its use also enables complex parallel programing errors such as races, communication errors, and deadlocks. Automatic tools can assist application developers in the detection and removal of such errors. This thesis considers tools that detect such errors during an application run and advanc

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Books on the topic "Classification correctness"

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Treatise on the Causes and Effects of Inflammation, Fever, Cancer, Scrofula, and Nervous Affections: Observations on the Correctness of Linnaeus's Classification of Diseases, Together with Remarks on the Specific Action of His Patent Medicated... Creative Media Partners, LLC, 2021.

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Book chapters on the topic "Classification correctness"

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Noster, Norbert, Arnon Hershkovitz, Michal Tabach, and Hans-Stefan Siller. "Learners’ Strategies in Interactive Sorting Tasks." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16290-9_21.

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AbstractUsing examples and non-examples is a common technique to demonstrate concepts’ characteristics and boundaries. Based on their properties, certain objects are accepted as examples or non-examples intuitively, while others are accepted or neglected non-intuitively. This 2*2 classification is powerful when designing technology-enhanced learning experiences in which feedback could be provided in real-time. That is, feedback could be based not only on the correctness of student response, but also on the specifics of the objects with which they were engaged. Following this framework, we deve

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Chalupa, Marek, Thomas A. Henzinger, Nicolas Mazzocchi, and N. Ege Saraç. "QuAK: Quantitative Automata Kit." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-75387-9_1.

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AbstractSystem behaviors are traditionally evaluated through binary classifications of correctness, which do not suffice for properties involving quantitative aspects of systems and executions. Quantitative automata offer a more nuanced approach, mapping each execution to a real number by incorporating weighted transitions and value functions generalizing acceptance conditions. In this paper, we introduce QuAK, the first tool designed to automate the analysis of quantitative automata. QuAK currently supports a variety of quantitative automaton types, including $${\textsf{Inf}}$$ Inf , $${\text

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Topalova Svetlana and Zhelezova Stela. "Classification of Doubly Resolvable Designs and Orthogonal Resolutions." In NATO Science for Peace and Security Series - D: Information and Communication Security. IOS Press, 2009. https://doi.org/10.3233/978-1-60750-002-5-260.

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We classify doubly resolvable designs with small parameters by a modification of a known algorithm for classification of the binary equidistant constant weight codes which correspond to resolvable designs with these parameters. For each of these designs we next construct all the sets of mutually orthogonal resolutions. We also derive lower bounds for some parameters beyond the application range of this general approach and check the correctness of the computational results in several ways.

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Noll, Richard, Mirjam Minor, Alexandra Berger, et al. "Conception, Development and Validation of Classification Methods for Coding Support of Rare Diseases Using Artificial Intelligence." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220755.

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Automated coding of diseases can support hospitals in the billing of inpatient cases with the health insurance funds. This paper describes the implementation and evaluation of classification methods for two selected Rare Diseases. Different classifiers of an off-the-shelf system and an own application are applied in a supervised learning process and comparatively examined for their suitability and reliability. Using Natural Language Processing and Machine Learning, disease entities are recognized from unstructured historical patient records and new billing cases are coded automatically. The re

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Borissov Yuri, Braeken An, Nikova Svetla, and Preneel Bart. "Classification of the Cosets of RM(1, 7) in RM(3, 7) Revisited." In NATO Science for Peace and Security Series - D: Information and Communication Security. IOS Press, 2008. https://doi.org/10.3233/978-1-58603-878-6-58.

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Based on classification of Boolean cubic forms of seven variables given by X.D. Hou in 1996, we show how to efficiently classify the cosets of RM(1, 7) in RM(3, 7) under the action of the general affine group AGL(7, 2). At the same time the sizes of the orbits are determined. We discuss also, the correctness of our computations.

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Ahmed Mobyen Uddin and Loutfi Amy. "Physical Activity Classification for Elderly Based on Pulse Rate." In Studies in Health Technology and Informatics. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-268-4-152.

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Physical activity is one of the key components for elderly in order to be actively ageing. However, it is difficult to differentiate and identify the body movement and actual physical activity using only accelerometer measurements. Therefore, this paper presents an application of a case-based retrieval classification scheme to classify the physical activity of elderly based on pulse rate measurements. Here, a case-based retrieval approach used the features extracted from both time and frequency domain. The evaluation result shows the best accuracy performance while considering the combination

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Martínez-Rodrigo Arturo, Fernández-Caballero Antonio, Silva Fábio, and Novais Paulo. "Monitoring Electrodermal Activity for Stress Recognition Using a Wearable." In Ambient Intelligence and Smart Environments. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-690-3-416.

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This paper introduces a novel and unobtrusive wearable monitoring device to be used for stress recognition. The paper offers details on the hardware design as well as on the software processes needed to classify between calm and stressed subjects. Only one physiological variable, the electrodermal activity, is used in this work. Moreover, the experimentation, training and testing of the mathematical classification model are also provided. A correctness of 82.5% is achieved by the combination of three skin conductivity response features. It is also interesting to highlight that the proposed app

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Ouedraogo, Moussa, Haralambos Mouratidis, Eric Dubois, and Djamel Khadraoui. "Security Assurance Evaluation and IT Systems’ Context of Use Security Criticality." In Mobile and Handheld Computing Solutions for Organizations and End-Users. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2785-7.ch005.

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Today’s IT systems are ubiquitous and take the form of small portable devices, to the convenience of the users. However, the reliance on this technology is increasing faster than the ability to deal with the simultaneously increasing threats to information security. This paper proposes metrics and a methodology for the evaluation of operational systems security assurance that take into account the measurement of security correctness of a safeguarding measure and the analysis of the security criticality of the context in which the system is operating (i.e., where is the system used and/or what

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Rastogi, Rohit, Devendra Kumar Chaturvedi, and Mayank Gupta. "Mental Health Through Biofeedback Is Important to Analyze." In Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2742-9.ch020.

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Many apps and analyzers based on machine learning have been designed to help and cure the stress issue. This chapter is based on an experiment that the authors performed at Research Labs and Scientific Spirituality Centers of Dev Sanskriti VishwaVidyalaya, Haridwar and Patanjali Research Foundations, Uttarakhand. In the research work, the correctness and accuracy have been studied and compared for two biofeedback devices named as electromyography (EMG) and galvanic skin response (GSR), which can operate in three modes: audio, visual and audio-visual with the help of data set of tension type he

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B., Suchitra, and Valarmathi V. "Acute Analysis of Bioinspired Optimization Algorithms for Diabetic Debrecen." In Intelligent Decision Making Through Bio-Inspired Optimization. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2073-0.ch004.

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Nature has all healing powers. Same way, nature is a basis of spur for resolving rigid and multifaceted problems Bio-inspired represents the parasol of diverse studies of computer science, mathematics, and biology in the last years. Bioinspired optmization algorithm is a developing approach that is based on the philosophies and motivation of the biological evolution of nature to develop new and robust challenging techniques. Biologically enthused computing and optimization is a foremost subclass of natural computation. This chapter presents a life-threatening survey of bio-inspired optimizatio

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Conference papers on the topic "Classification correctness"

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Manyam, Yashaswini, Srinidhi Sundaram, Roshni M. Balakrishnan, and Peeta Basa Pati. "Analysis Of The Efficiency of MathBERT and T5 Embeddings in Classification of Students’ Responses to Algebraic Questions based on their Correctness and Relevance." In 2024 5th IEEE Global Conference for Advancement in Technology (GCAT). IEEE, 2024. https://doi.org/10.1109/gcat62922.2024.10923960.

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Lo, Shu-chuan. "The effects of feature selection and model selection on the correctness of classification." In EM). IEEE, 2010. http://dx.doi.org/10.1109/ieem.2010.5674225.

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Vieira, Ana Sofia. "Consistency Management in Feature-Based Parametric Design." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0237.

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Abstract One of the main problems to be solved in design-by-features is to preserve the semantic correctness of feature-based models. Currently, feature-based parametric design (FbPD) is being used as one of the most powerful approaches for solving this problem. In this paper, a fundamental principle of this approach is introduced. Three aspects stated, are: FbPD deals with functional design primitives, it solves the automatic generation of model variations, and it offers the basis for the development of a mechanism to check the semantic correctness of feature-based models. Several concepts fo

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Christakis, Maria, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, and Valentin Wüstholz. "Specifying and Testing k-Safety Properties for Machine-Learning Models." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/528.

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Machine-learning models are becoming increasingly prevalent in our lives, for instance assisting in image-classification or decision-making tasks. Consequently, the reliability of these models is of critical importance and has resulted in the development of numerous approaches for validating and verifying their robustness and fairness. However, beyond such specific properties, it is challenging to specify, let alone check, general functional-correctness expectations from models. In this paper, we take inspiration from specifications used in formal methods, expressing functional-correctness pro

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Xiong, Haoyi, Wei Cheng, Yanjie Fu, Wenqing Hu, Jiang Bian, and Zhishan Guo. "De-biasing Covariance-Regularized Discriminant Analysis." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/401.

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Fisher's Linear Discriminant Analysis (FLD) is a well-known technique for linear classification, feature extraction and dimension reduction. The empirical FLD relies on two key estimations from the data -- the mean vector for each class and the (inverse) covariance matrix. To improve the accuracy of FLD under the High Dimension Low Sample Size (HDLSS) settings, Covariance-Regularized FLD (CRLD) has been proposed to use shrunken covariance estimators, such as Graphical Lasso, to strike a balance between biases and variances. Though CRLD could obtain better classification accuracy, it usually in

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Kiersztyn, Adam, Rafal Lopucki, Krystyna Kiersztyn, et al. "A Comprehensive Analysis of the Impact of Selecting the Training Set Elements on the Correctness of Classification for Highly Variable Ecological Data." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494399.

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Staab, Sergio, Ludger Martin, Johannes Luderschmidt, and Simon Krissel. "Prediction accuracy comparison between deep learning and classification algorithms in the context of human activity recognition." In 8th International Conference on Human Interaction and Emerging Technologies. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002747.

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In this paper, we compare the prediction accuracy of a deep learning model and three classification algorithms on very similar motions in the field of dementia diagnostics.The basic aim is to gain insights into the retrieval, provision and classification of interaction and health data in the course of the disease of dementia patients. This work shows how the smartwatch "Apple Watch Series 7" can be used to record interaction data from dementia patients and recognise corresponding movement sequences.A data transfer platform was developed that enables communication with a watchOS application on

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Demajo, Lara Marie, Vince Vella, and Alexiei Dingli. "Explainable AI for Interpretable Credit Scoring." In 10th International Conference on Advances in Computing and Information Technology (ACITY 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101516.

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With the ever-growing achievements in Artificial Intelligence (AI) and the recent boosted enthusiasm in Financial Technology (FinTech), applications such as credit scoring have gained substantial academic interest. Credit scoring helps financial experts make better decisions regarding whether or not to accept a loan application, such that loans with a high probability of default are not accepted. Apart from the noisy and highly imbalanced data challenges faced by such credit scoring models, recent regulations such as the `right to explanation' introduced by the General Data Protection Regulati

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Trivedi, Shubham, and Ramya Hebbale Ramkumar. "Applying AI to Reduce Software Testing Defects’ Rejection." In 11th SAEINDIA International Mobility Conference (SIIMC 2024). SAE International, 2024. https://doi.org/10.4271/2024-28-0188.

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<div class="section abstract"><div class="htmlview paragraph">The efficiency and accuracy of defect control are critical components in software testing, as they determine the final product's quality and cost. Rejection of defects for various reasons, like non-reproducibility, erroneous classification or inadequate information, is one of the largest issues that testers face. This paper presents an AI-driven approach that reduces the number of defect rejections by using the past defect data to give testers real-time advises and warnings.</div><div class="htmlview paragraph"&

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Mossa, Ashley, and Rupert Weston. "Lessons Learned in Reviewing CCF Events." In 17th International Conference on Nuclear Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/icone17-75887.

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The U.S. Nuclear Regulatory Commission (NRC) has an ongoing Common Cause Failure (CCF) data analysis program that periodically collects and evaluates information on component failures at U.S. commercial Nuclear Power Plants (NPPs). The primary information sources include the Licensee Event Reports (LER) and records from the Equipment Performance Information Exchange (EPIX) program. Once the information is collected, the failure records are evaluated to identify potential CCF events. CCF events are then coded, reviewed, and loaded into the NRC’s database. Verification of the CCF events is perfo

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Reports on the topic "Classification correctness"

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Bilyk, Zhanna I., Yevhenii B. Shapovalov, Viktor B. Shapovalov, Anna P. Megalinska, Fabian Andruszkiewicz, and Agnieszka Dołhańczuk-Śródka. Assessment of mobile phone applications feasibility on plant recognition: comparison with Google Lens AR-app. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4403.

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The paper is devoted to systemizing all mobile applications used during the STEM-classes and can be used to identify plants. There are 10 mobile applications that are plant identifiers worldwide. These applications can be divided into three groups, such as plant identifiers that can analyze photos, plant classification provides the possibility to identify plants manually, plants-care apps that remind water of the plant, or change the soil. In this work, mobile apps such as Flora Incognita, PlantNet, PlantSnap, PictureThis, LeafSnap, Seek, PlantNet were analyzed for usability parameters and acc

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