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Tytuł:
Zastosowanie termowizji do detekcji nieszczelności w sektorze motoryzacyjnym
The Use of Thermovision for Leak Detection in the Automotive Sector
Autorzy:
Macherzyński, Wojciech
Ochman, Marcin
Kulas, Zbigniew
Dudek, Krzysztof
Didyk, Mateusz
Sroczyński, Dawid
Powiązania:
https://bibliotekanauki.pl/articles/2068624.pdf
Data publikacji:
2021
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
detekcja nieszczelności
lokalizacja nieszczelności
termowizja
algorytm klasyfikacji nieszczelności
leakage detection
leakage localization
thermovision
leakage classification algorithm
Opis:
Coraz bardziej rygorystyczne wymagania w zakresie ochrony środowiska, bezpieczeństwa czy niezawodności wymuszają na firmach z sektora motoryzacyjnego stosowanie efektywniejszych testów potwierdzających wymaganą szczelności komponentów (chłodnic, zbiorników, sprężyn powietrznych itp.). Obecnie stosowane metody niosą ze sobą ograniczenia, które generują otwartość przemysłu motoryzacyjnego na zupełnie nowe sposoby realizacji pomiaru nieszczelności. Zastosowanie kamer termowizyjnych do pomiaru energii cieplnej jest obecnie powszechną praktyką w wielu dziedzinach, a zastosowanie ich do pomiaru nieszczelności zamkniętych ustrojów pozwoliłoby na znaczne skrócenie czasu pomiarów w przypadku zbiorników odkształcalnych, wymagających długich czasów stabilizacji w metodach konkurencyjnych. W artykule opisano zastosowanie termowizji do wykrywania nieszczelności sprężyn gazowych.
Increasing requirements for environmental protection, safety or reliability force automotive industries to use more efficient tests to measure tightness of the components. Currently adapted methods brings limitations which makes automotive industry open for new techniques for leakage tests. Infrared cameras are widely used in various fields. Using them to test leakage of closed-volume systems allows to significantly reduce test time, especially for objects which requires long stabilization times in competitive methods. In the article thermovision usage for leakage detection of gas springs were described.
Źródło:
Pomiary Automatyka Robotyka; 2021, 25, 3; 79--85
1427-9126
Pojawia się w:
Pomiary Automatyka Robotyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Web–based framework for breast cancer classification
Autorzy:
Bruździński, T.
Krzyżak, A.
Fevens, T.
Jeleń, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/91866.pdf
Data publikacji:
2014
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
breast cancer
classification
cytological image
aspiration biopsy
feature vector
classifier
multilayer perceptron
segmentation algorithm
Opis:
The aim of this work is to create a web-based system that will assist its users in the cancer diagnosis process by means of automatic classification of cytological images obtained during fine needle aspiration biopsy. This paper contains a description of the study on the quality of the various algorithms used for the segmentation and classification of breast cancer malignancy. The object of the study is to classify the degree of malignancy of breast cancer cases from fine needle aspiration biopsy images into one of the two classes of malignancy, high or intermediate. For that purpose we have compared 3 segmentation methods: k-means, fuzzy c-means and watershed, and based on these segmentations we have constructed a 25–element feature vector. The feature vector was introduced as an input to 8 classifiers and their accuracy was checked. The results show that the highest classification accuracy of 89.02 % was recorded for the multilayer perceptron. Fuzzy c–means proved to be the most accurate segmentation algorithm, but at the same time it is the most computationally intensive among the three studied segmentation methods.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 2; 149-162
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of Gabor filters for texture classification of airborne images and LiDAR data
Autorzy:
Marmol, U.
Powiązania:
https://bibliotekanauki.pl/articles/130042.pdf
Data publikacji:
2011
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
texture analysis
lidar
algorithm
automated classification
analiza tekstury
LIDAR
algorytm
klasyfikacja automatyczna
Opis:
In this paper, a texture approach is presented for building and vegetation extraction from LIDAR and aerial images. The texture is very important attribute in many image analysis or computer vision applications. The procedures developed for texture problem can be subdivided into four categories: structural approach, statistical approach, model based approach and filter based approach. In this paper, different definitions of texture are described, but complete emphasis is given on filter based methods. Examples of filtering methods are Fourier transform, Gabor and wavelet transforms. Here, Gabor filter is studied and its implementation for texture analysis is explored. This approach is inspired by a multi-channel filtering theory for processing visual information in the human visual system. This theory holds that visual system decomposes the image into a number of filtered images of a specified frequency, amplitude and orientation. The main objective of the article is to use Gabor filters for automatic urban object and tree detection. The first step is a definition of Gabor filter parameters: frequency, standard deviation and orientation. By varying these parameters, a filter bank is obtained that covers the frequency domain almost completely. These filters are used to aerial images and LIDAR data. The filtered images that possess a significant information about analyzed objects are selected, and the rest are discarded. Then, an energy measure is defined on the filtered images in order to compute different texture features. The Gabor features are used to image segmentation using thresholding. The tests were performed using set of images containing very different landscapes: urban area and vegetation of varying configurations, sizes and shapes of objects. The performed studies revealed that textural algorithms have the ability to detect buildings and trees. This article is the attempt to use texture methods also to LIDAR data, resampling into regular grid cells. The obtained preliminary results are interesting.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2011, 22; 325-336
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Towards a very fast feedforward multilayer neural networks training algorithm
Autorzy:
Bilski, Jarosław
Kowalczyk, Bartosz
Kisiel-Dorohinicki, Marek
Siwocha, Agnieszka
Żurada, Jacek
Powiązania:
https://bibliotekanauki.pl/articles/2147135.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
neural network training algorithm
QR decomposition
scaled Givens rotation
approximation
classification
Opis:
This paper presents a novel fast algorithm for feedforward neural networks training. It is based on the Recursive Least Squares (RLS) method commonly used for designing adaptive filters. Besides, it utilizes two techniques of linear algebra, namely the orthogonal transformation method, called the Givens Rotations (GR), and the QR decomposition, creating the GQR (symbolically we write GR + QR = GQR) procedure for solving the normal equations in the weight update process. In this paper, a novel approach to the GQR algorithm is presented. The main idea revolves around reducing the computational cost of a single rotation by eliminating the square root calculation and reducing the number of multiplications. The proposed modification is based on the scaled version of the Givens rotations, denoted as SGQR. This modification is expected to bring a significant training time reduction comparing to the classic GQR algorithm. The paper begins with the introduction and the classic Givens rotation description. Then, the scaled rotation and its usage in the QR decomposition is discussed. The main section of the article presents the neural network training algorithm which utilizes scaled Givens rotations and QR decomposition in the weight update process. Next, the experiment results of the proposed algorithm are presented and discussed. The experiment utilizes several benchmarks combined with neural networks of various topologies. It is shown that the proposed algorithm outperforms several other commonly used methods, including well known Adam optimizer.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 181--195
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The PM-M prototype selection system
Autorzy:
Grudziński, K.
Powiązania:
https://bibliotekanauki.pl/articles/206602.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
selection of reference instances
prototype selection
k-Nearest Neighbors algorithm
classification of data
Opis:
In this paper, the algorithm, realizing the author’s prototype selection method, called PM-M (Partial Memory - Minimization) is described in details. Computational experiments that have been carried out with the raw PM-M model and with its majority ensembles indicate that even for the system, for which the average size of the selected prototype sets constitutes only about five percent of the size of the original training datasets, the obtained results of classification are still in a good statistical agreement with the 1-Nearest Neighbor (IB1) model which has been trained on the original (i.e. unpruned) data. It has also been shown that the system under study is competitive in terms of generalization ability with respect to other well established prototype selection systems, such as, for example, CHC, SSMA and GGA. Moreover, the proposed algorithm has shown approximately one to three orders of magnitude decrement of time requirements with respect to the necessary time, needed to complete the calculations, relative to the reference prototype classifiers, taken for comparison. It has also been demonstrated that the PM-M system can be directly applied to analysis of very large data unlike most other prototype methods, which have to rely on the stratification approach.
Źródło:
Control and Cybernetics; 2016, 45, 4; 539-561
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Support Vector Machine based Decoding Algorithm for BCH Codes
Autorzy:
Sudharsan, V.
Yamuna, B.
Powiązania:
https://bibliotekanauki.pl/articles/958048.pdf
Data publikacji:
2016
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
BCH codes
Chase-2 algorithm
coding gain
kernel
multi-class classification
Soft Decision Decoding
Support Vector Machine
Opis:
Modern communication systems require robust, adaptable and high performance decoders for efficient data transmission. Support Vector Machine (SVM) is a margin based classification and regression technique. In this paper, decoding of Bose Chaudhuri Hocquenghem codes has been approached as a multi-class classification problem using SVM. In conventional decoding algorithms, the procedure for decoding is usually fixed irrespective of the SNR environment in which the transmission takes place, but SVM being a machinelearning algorithm is adaptable to the communication environment. Since the construction of SVM decoder model uses the training data set, application specific decoders can be designed by choosing the training size efficiently. With the soft margin width in SVM being controlled by an equation, which has been formulated as a quadratic programming problem, there are no local minima issues in SVM and is robust to outliers.
Źródło:
Journal of Telecommunications and Information Technology; 2016, 2; 108-112
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reinforcement-Based Learning for Process Classification Task
Autorzy:
Bashir, Lubna Zaghlul
Powiązania:
https://bibliotekanauki.pl/articles/1192874.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Reinforcement Learning
Reward
Classification
Bucket Brigade Algorithm
Opis:
In this work, we present a reinforcement-based learning algorithm that includes the automatic classification of both sensors and actions. The classification process is prior to any application of reinforcement learning. If categories are not at the adequate abstraction level, the problem could be not learnable. The classification process is usually done by the programmer and is not considered as part of the learning process. However, in complex tasks, environments, or agents, this manual process could become extremely difficult. To solve this inconvenience, we propose to include the classification into the learning process. We apply an algorithm to automatically learn to achieve a task through reinforcement learning that works without needing a previous classification process. The system is called Fish or Ship (FOS) assigned the task of inducing classification rules for classification task described in terms of 6 attributes. The task is to categorize an object that has one or more of the following features: Sail, Solid, Big, Swim, Eye, Fins into one of the following: fish, or ship. First results of the application of this algorithm are shown Reinforcement learning techniques were used to implement classification task with interesting properties such as provides guidance to the system and shortening the number of cycles required to learn.
Źródło:
World Scientific News; 2016, 36; 12-26
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Patient classification algorithm at urgency care area of a hospital based on the triage system
Autorzy:
Mondragon, N.
Istrate, D.
Wegrzyn-Wolska, K.
Garcia, J. C.
Sanchez, J.C.
Powiązania:
https://bibliotekanauki.pl/articles/951692.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
triage
classification
SET
fuzzy logic
decision trees
patients
urgency
hospital emergency
algorithm
ocena stanu zdrowia rannych
klasyfikacja
logika rozmyta
drzewa decyzyjne
pacjenci
pomoc szpitalna
algorytm
Opis:
The time passed in the urgency zone of a hospital is really important, and the quick evaluation and selection of the patients who arrive to this area is essential to avoid waste of time and help the patients in a higher emergency level. The triage, an evaluation and classification structured system, allows to manage the urgency level of the patient; it is based on the vital signs measures and clinical data of the patient. The goal is making the classification in the shortest possible time and with a minimal error percentage. Levels are allocated according to the concept that what is urgent is not always serious and that what is serious is not always urgent. In this work, we present a computational algorithm that evaluates the patients within the fever symptomatic category, we use fuzzy logic and decision trees to collect and analyze simultaneously the vital signs and the clinical data of the patient through a graphical interface; so that the classification can be more intuitive and faster. Fuzzy logic allows us to process data and take a decision based on incomplete information or uncertain values, decision trees are structures or rules sets that classify the data when we have several variables.
Źródło:
Journal of Medical Informatics & Technologies; 2013, 22; 87-94
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimising a fuzzy fault classification tree by a single-objective genetic algorithm
Autorzy:
Zio, E.
Baraldi, P.
Popescu, I. C.
Powiązania:
https://bibliotekanauki.pl/articles/2069595.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:
fault classification
decision tree
fuzzy logic
genetic algorithm
Opis:
In this paper a single-objective Genetic Algorithm is exploited to optimise a Fuzzy Decision Tree for fault classification. The optimisation procedure is presented with respect to an ancillary classification problem built with artificial data. Work is in progress for the application of the proposed approach to a real fault classification problem.
Źródło:
Journal of Polish Safety and Reliability Association; 2007, 2; 391--400
2084-5316
Pojawia się w:
Journal of Polish Safety and Reliability Association
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Online Training and Contests for Informatics Contestants of Secondary School Age
Autorzy:
NÉMETH,, Ágnes Erdősné
ZSAKÓ, László
Powiązania:
https://bibliotekanauki.pl/articles/457559.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Rzeszowski
Tematy:
algorithm
online contest
online training
classification
IOI
Opis:
If you prepare students for programming contests carefully selected and widely available online training and contests offer help and diversity. If you teach about testing programs you have to know which sites offer downloadable tests or feedback with detailed test cases. If you want to make series of tasks for practicing you have to know which sites offer you categorized tasks of the appropriate level. In order to be able to choose from the available materials we need to categorize them. The previously defined and used criteria need some supplement criteria for better and sophisticated use of categorization from the teacher’s point of view. Online resources can be classified in general: what programming languages can be used, how often the contests are organized, in which languages they can be accessed, what types of problems a website deals with and at what level, what prior knowledge is required. We can group sites according to whether they help teachers to set tasks for their students, or get ideas for solutions or see the results of their students. Online contests can also be categorized regarding whether students can see each other's solutions. The aim of this paper is to supplement the categorization and describe some major portals according to the previously defined and supplemented criteria.
Źródło:
Edukacja-Technika-Informatyka; 2015, 6, 1; 273-280
2080-9069
Pojawia się w:
Edukacja-Technika-Informatyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Music Playlist Generation using Facial Expression Analysis and Task Extraction
Autorzy:
Sen, A.
Popat, D.
Shah, H.
Kuwor, P.
Johri, E.
Powiązania:
https://bibliotekanauki.pl/articles/908868.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
facial expression analysis
emotion recognition
feature extraction
viola jones face detection
gabor filter
adaboost
k-NN algorithm
task extraction
music classification
playlist generation
Opis:
In day to day stressful environment of IT Industry, there is a truancy for the appropriate relaxation time for all working professionals. To keep a person stress free, various technical or non-technical stress releasing methods are now being adopted. We can categorize the people working on computers as administrators, programmers, etc. each of whom require varied ways in order to ease themselves. The work pressure and the vexation of any kind for a person can be depicted by their emotions. Facial expressions are the key to analyze the current psychology of the person. In this paper, we discuss a user intuitive smart music player. This player will capture the facial expressions of a person working on the computer and identify the current emotion. Intuitively the music will be played for the user to relax them. The music player will take into account the foreground processes which the person is executing on the computer. Since various sort of music is available to boost one's enthusiasm, taking into consideration the tasks executed on the system by the user and the current emotions they carry, an ideal playlist of songs will be created and played for the person. The person can browse the playlist and modify it to make the system more flexible. This music player will thus allow the working professionals to stay relaxed in spite of their workloads.
Źródło:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2016, 16, 2; 1-6
1732-1360
2083-3628
Pojawia się w:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset
Autorzy:
Mosavi, Mohammad Reza
Khishe, Mohammad
Naseri, Mohammad Jafar
Parvizi, Gholam Reza
Ayat, Mehdi
Powiązania:
https://bibliotekanauki.pl/articles/176971.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
MLP NN
Multi-Layer Perceptron Neural Network
ABGSA
Adaptive Best Mass Gravitational Search Algorithm
sonar
classification
Opis:
In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.
Źródło:
Archives of Acoustics; 2019, 44, 1; 137-151
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Monitoring of Land Surface Temperature from Landsat Imagery: A Case Study of Al-Anbar Governorate in Iraq
Autorzy:
Morsy, Salem
Ahmed, Shaker
Powiązania:
https://bibliotekanauki.pl/articles/2203961.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
land surface temperature
Landsat
single channel algorithm
NDVI
land use
land cover
classification
regression
Opis:
Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST estimation and monitoring of the main part of Al-Anbar Governorate in Iraq is presented using Landsat imagery from five years (2005, 2010, 2015, 2016 and 2020). Images of the years 2005 and 2010 were captured by Landsat 5 (TM) and the others were captured by Landsat 8 (OLI/TIRS). The Single Channel Algorithm was applied to retrieve the LST from Landsat 5 and Landsat 8 images. Moreover, the land use/land cover (LULC) maps were developed for the five years using the maximum likelihood classifier. The difference in the LST and normalized difference vegetation index (NDVI) values over this period was observed due to the changes in LULC. Finally, a regression analysis was conducted to model the relationship between the LST and NDVI. The results showed that the highest LST of the study area was recorded in 2016 (min = 21.1°C, max = 53.2°C and mean = 40.8°C). This was attributed to the fact that many people were displaced and had left their agricultural fields. Therefore, thousands of hectares of land which had previously been green land became desertified. This conclusion was supported by comparing the agricultural land areas registered throughout the presented years. The polynomial regression analysis of LST and NDVI revealed a better coefficient of determination (R2) than the linear regression analysis with an average R2 of 0.423.
Źródło:
Geomatics and Environmental Engineering; 2023, 17, 3; 61--81
1898-1135
Pojawia się w:
Geomatics and Environmental Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Model klasyfikacji wiedzy w przedsiębiorstwie produkcyjnym przy zastosowaniu algorytmu Bayes’a
Autorzy:
Dudek, A.
Patalas-Maliszewska, J.
Powiązania:
https://bibliotekanauki.pl/articles/118404.pdf
Data publikacji:
2016
Wydawca:
Politechnika Koszalińska. Wydawnictwo Uczelniane
Tematy:
model klasyfikacji wiedzy
gromadzenie danych
algorytm Bayes’a
model knowledge classification
collect data
Bayesian algorithm
Opis:
W artykule podjęto próbę zbudowania modelu klasyfikacji wiedzy w przedsiębiorstwie produkcyjnym w oparciu o algorytm Bayes’a. Pozyskiwanie, gromadzenie i przechowywanie danych i informacji działu obsługi serwisowej, możliwe jest za pomocą autorskiej aplikacji, której struktura została również przedstawiona w niniejszym artykule. Na podstawie danych i informacji zawartych w zgłoszeniach serwisowych, rejestrowanych w aplikacji, możliwe jest generowanie zdefiniowanej wiedzy. W konsekwencji, proponowany model klasyfikacji wiedzy, przy zastosowaniu algorytmu Bayes’a, daje możliwość zbudowania zbiorów użytecznej wiedzy.
This article elaborates a model of knowledge classification using a Bayesian algorithm in a manufacturing company. Further was illustrated an application, that enables you to collect, search and analyze data and information from a service department. Based on the data and information registered in the application, it is possible to generate a defined knowledge. Consequently, the proposed model for the classification of knowledge, using a Bayesian algorithm gives the opportunity to build the sets of useful knowledge.
Źródło:
Zeszyty Naukowe Wydziału Elektroniki i Informatyki Politechniki Koszalińskiej; 2016, 9; 85-98
1897-7421
Pojawia się w:
Zeszyty Naukowe Wydziału Elektroniki i Informatyki Politechniki Koszalińskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Metrics and similarities in modeling dependencies between continuous and nominal data
Autorzy:
Grabowski, M.
Korpusik, M.
Powiązania:
https://bibliotekanauki.pl/articles/91361.pdf
Data publikacji:
2013
Wydawca:
Warszawska Wyższa Szkoła Informatyki
Tematy:
k-nearest neighbors algorithm
data metrics
classification
continuous data
nominal data
Opis:
Classification theory analytical paradigm investigates continuous data only. When we deal with a mix of continuous and nominal attributes in data records, difficulties emerge. Usually, the analytical paradigm treats nominal attributes as continuous ones via numerical coding of nominal values (often a bit ad hoc). We propose a way of keeping nominal values within analytical paradigm with no pretending that nominal values are continuous. The core idea is that the information hidden in nominal values influences on metric (or on similarity function) between records of continuous and nominal data. Adaptation finds relevant parameters which influence metric between data records. Our approach works well for classifier induction algorithms where metric or similarity is generic, for instance k nearest neighbor algorithm or proposed here support of decision tree induction by similarity function between data. The k-nn algorithm working with continuous and nominal data behaves considerably better, when nominal values are processed by our approach. Algorithms of analytical paradigm using linear and probability machinery, like discriminant adaptive nearest-neighbor or Fisher’s linear discriminant analysis, cause some difficulties. We propose some possible ways to overcome these obstacles for adaptive nearest neighbor algorithm.
Źródło:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2013, 7, 10; 25-37
1896-396X
2082-8349
Pojawia się w:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 33

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