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Tytuł:
Friedman and Wilcoxon Evaluations Comparing SVM, Bagging, Boosting, K-NN and Decision Tree Classifiers
Autorzy:
Biju, V. G.
Prashanth, CM
Powiązania:
https://bibliotekanauki.pl/articles/108646.pdf
Data publikacji:
2017
Wydawca:
Społeczna Akademia Nauk w Łodzi
Tematy:
bagging
boosting
SVM
KNN
decision tree
Opis:
This paper describes a number of experiments to compare and validate the performance of machine learning classifiers. Creating machine learning models for data with wide varieties has huge applications in predictive modelling across multiple domain of science. This work reviews state of the art techniques in machine learning classifiers methods with several extent of magnitude in statistics and key findings that will be helpful in establishing best methodological practices for class predictions. Comprehensive comparative review analysis with statistical validations for various machine learning algorithm for SVM, Bagging, Boosting, Decision Trees and Nearest Neighborhood algorithm on multiple data sets is carried out. Focus on the statistical analysis of the results using Friedman-Test and Wilcoxon Test as well as other interpretative metrics like classification rate, ROC, F-measure are evaluated to benchmark results.
Źródło:
Journal of Applied Computer Science Methods; 2017, 9 No. 1; 23-47
1689-9636
Pojawia się w:
Journal of Applied Computer Science Methods
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of complex decision problems based on cumulative prospect theory
Autorzy:
Dudzińska-Baryła, R.
Powiązania:
https://bibliotekanauki.pl/articles/406332.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
cumulative prospect theory
complex decision problem
decision tree
Opis:
Complex risky decision problems involve sequences of decisions and random events. The choice at a given stage depends on the decisions taken in the previous stages, as well as on the realizations of the random events that occurred earlier. In the analysis of such situations, decision trees are used, and the criterion for choosing the optimal decision is to maximize the expected monetary value. Unfortunately, this approach often does not reflect the actual choices of individual decision makers. In descriptive decision theory, the criterion of maximizing the expected monetary value is replaced by a subjective valuation that takes into account the relative outcomes and their probabilities. This paper presents a proposal to use the principles of cumulative prospect theory to analyse complex decision problems. The concept of a certainty equivalent is used to make it possible to compare risky and non-risky alternatives.
Źródło:
Operations Research and Decisions; 2018, 28, 3; 5-16
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Features of Creating a System of Space Monitoring of Water-Supplied Territories for Irrigation in the South of Kazakhstan
Autorzy:
Malakhov, Dmitry V.
Tskhay, Mikhail
Kalashnikov, Alexander A.
Bekmukhamedov, Nurlan E.
Kalashnikov, Pavel A.
Baizakova, Aigul
Powiązania:
https://bibliotekanauki.pl/articles/2202277.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
irrigation
spectral indices
decision tree
monitoring
evaluation
Opis:
The location of a significant part of the agricultural territories of Kazakhstan in the risk agriculture zone implies the development and further application of an objective monitoring system for irrigated territories. The purpose of the study was to develop methods for on-the-spot and long-term recognition of irrigated massifs and verification of methods in the conditions of the territories of southern Kazakhstan. The paper describes the methods of on-the-spot recognition of irrigated fields, the general assessment of irrigated areas for the growing season, as well as the method of recognizing promising areas for irrigation. The on-the-spot recognition of the fields is based on the use of such spectral indices as the Global Vegetation Moisture Index, Green Normalized Difference Vegetation Index, Normalized Difference Vegetation Index, and the xanthophyll index, combined into a single system by the Decision Tree algorithm. The assessment of irrigated areas is based on differences in the physiological state of plants in conditions of normal water supply and plants experiencing a lack of moisture. The evaluation system includes the calculation of the temperature difference according to the corresponding satellite data and the calculation of the difference in vegetation indices for the same period. The difference in vegetation indices in irrigated fields has positive values due to a steady increase in green biomass, and the temperature difference, on the contrary, is negative or zero, since healthy plants, with normal water supply, actively evaporate moisture to maintain optimal temperatures of biochemical processes. To develop these methods, ground data from 2017–2021 were used. Verification of the methods with ground data demonstrated acceptable accuracy (87% in the on-the-spot assessment of irrigated fields; 60–90% in the general assessment of irrigated areas), while the methods have significant potential for further improvement.
Źródło:
Journal of Ecological Engineering; 2022, 23, 11; 202--216
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hardware implementation of a decision tree classifier for object recognition applications
Autorzy:
Fularz, M.
Kraft, M.
Powiązania:
https://bibliotekanauki.pl/articles/114595.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
decision tree
hardware implementation
FPGA
object recognition
Opis:
Hardware implementation of a widely used decision tree classifier is presented in this paper. The classifier task is to perform image-based object classification. The performance evaluation of the implemented architecture in terms of resource utilization and processing speed are reported. The presented architecture is compact, flexible and highly scalable and compares favorably to software-only solutions in terms of processing speed and power consumption.
Źródło:
Measurement Automation Monitoring; 2015, 61, 7; 379-381
2450-2855
Pojawia się w:
Measurement Automation Monitoring
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Methods of Classification of the Genera and Species of Bacteria Using Decision Tree
Autorzy:
Plichta, Anna
Powiązania:
https://bibliotekanauki.pl/articles/308707.pdf
Data publikacji:
2019
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
bacterial genera and species
decision tree
pattern recognition
Opis:
This paper presents a computer-based method for recognizing digital images of bacterial cells. It covers automatic recognition of twenty genera and species of bacteria chosen by the author whose original contribution to the work consisted in the decision to conduct the process of recognizing bacteria using the simultaneous analysis of the following physical features of bacterial cells: color, size, shape, number of clusters, cluster shape, as well as density and distribution of the cells. The proposed method may be also used to recognize the microorganisms other than bacteria. In addition, it does not require the use of any specialized equipment. The lack of demand for high infrastructural standards and complementarity with the hardware and software widens the scope of the method’s application in diagnostics, including microbiological diagnostics. The proposed method may be used to identify new genera and species of bacteria, but also other microorganisms that exhibit similar morphological characteristics.
Źródło:
Journal of Telecommunications and Information Technology; 2019, 4; 74-82
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automated root cause analysis of non-conformities with machine learning algorithms
Autorzy:
Mueller, T.
Greipel, J.
Weber, T.
Schmitt, R. H.
Powiązania:
https://bibliotekanauki.pl/articles/99625.pdf
Data publikacji:
2018
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
root cause analysis
machine learning
decision tree
simulation
Opis:
To detect root causes of non-conforming parts - parts outside the tolerance limits - in production processes a high level of expert knowledge is necessary. This results in high costs and a low flexibility in the choice of personnel to perform analyses. In modern production a vast amount of process data is available and machine learning algorithms exist which model processes empirically. Aim of this paper is to introduce a procedure for an automated root cause analysis based on machine learning algorithms to reduce the costs and the necessary expert knowledge. Therefore, a decision tree algorithm is chosen. A procedure for its application in an automated root cause analysis is presented and simulations to prove its applicability are conducted. In this paper influences affecting the success of detection are identified and simulated e.g. the necessary amount of data dependent on the amount of variables, the ratio between categories of non-conformities and OK parts as well as detectable root causes. The simulations are based on a regression model to determine the roughness of drilling holes. They prove the applicability of machine learning algorithms for an automated root cause analysis and indicate which influences have to be considered in real scenarios.
Źródło:
Journal of Machine Engineering; 2018, 18, 4; 60-72
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
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:
Application of sample advisory systems in medicine
Autorzy:
Woehl, Agnieszka
Zapotoczny, Kacper
Żaba, Julia
Nagi, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/34656174.pdf
Data publikacji:
2023
Wydawca:
Politechnika Opolska
Tematy:
advisory system
expert system
block diagram
decision tree
Opis:
Artificial intelligence is a field that has been rapidly developing in various areas of knowledge in recent years. Its application in medicine can support the intensive development of research in health care and improve and ac-celerate the operation of many medical facilities. This article presents sev-eral examples of expert systems that can find application in diagnosing and preparing a patient for selected tests. Expert systems can also find appli-cation in the rapid selection of rehabilitation, medical or support equip-ment and devices with which medical facilities are supplied. In this article, the reader will also find a sample application that will perform this func-tion. The article presents the elements of which a correct expert system should consist. For each application, tests have been carried out to show the correctness of the system. The purpose of the article was to show the capabilities of the expert system and its application in medical fields.
Źródło:
Sustainable Production, Instrumentation and Engineering Sciences; 2023, 1, 1; 13-17
2956-6711
Pojawia się w:
Sustainable Production, Instrumentation and Engineering Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Computational Intelligence for Analysing the Mechanical Properties of AA 2219 - (B4C + h-BN) Hybrid Nano Composites Processed by Ultrasound Assisted Casting
Autorzy:
Radha, P.
Selvakumar, N.
Harichandran, R.
Powiązania:
https://bibliotekanauki.pl/articles/354927.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
powder metallurgy
soft computing
ANN
fuzzy logic
decision tree
Opis:
The computational intelligence tool has major contribution to analyse the properties of materials without much experimentation. The B4 C particles are used to improve the quality of the strength of materials. With respect to the percentage of these particles used in the micro and nano, composites may fix the mechanical properties. The different combinations of input parameters determine the characteristics of raw materials. The load, content of B4 C particles with 0%, 2%, 4%, 6%, 8% and 10% will determine the wear behaviour like CoF, wear rate etc. The properties of materials like stress, strain, % of elongation and impact energy are studied. The temperature based CoF and wear rate is analysed. The temperature may vary between 30°C, 100°C and 200°C. In addition, the CoF and wear rate of materials are predicted with respect to load, weight % of B4 C and nano hexagonal boron nitride %. The intelligent tools like Neural Networks (BPNN, RBNN, FL and Decision tree) are applied to analyse these characteristics of micro/nano composites with the inclusion of B4 C particles and nano hBN % without physically conducting the experiments in the Lab. The material properties will be classified with respect to the range of input parameters using the computational model.
Źródło:
Archives of Metallurgy and Materials; 2019, 64, 3; 1163-1173
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Metody uczenia maszynowego w prognozowaniu niewypłacalności
Machine learning methods in bankruptcy prediction
Autorzy:
Paliński, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/589477.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Drzewo klasyfikacyjne
Prognozowanie
Uczenie maszynowe
Upadłość
Bankruptcy
Decision tree
Forecasting
Machine learning
Opis:
W artykule zastosowano wybrane algorytmy uczenia maszynowego na zbiorach danych zawierających wskaźniki finansowe w celu sprawdzenia skuteczności prognozowania upadłości. Trafność prognoz upadłości na zbiorach niezbilansowanych o przeważającym udziale firm prowadzących działalności nad upadłymi wyniosła jedynie 37%. Trafność prognozowania upadłości na zbiorach zbilansowanych wyniosła 60%. Dla porównania, uproszczone podejście eksperckie wyłoniło 76% spośród upadłych podmiotów, ale znacząco zawyżyło zbiór firm zagrożonych upadłością. Metody uczenia maszynowego okazują się skuteczne dla dużych zbiorów danych, które są zbyt liczne do analizy przez człowieka.
The article uses selected machine learning algorithms on datasets containing financial ratios to check the effectiveness of bankruptcy prediction. The accuracy of bankruptcy forecasts for unbalanced dataset with the prevalence of companies still operating over bankrupts was only 37%. The accuracy of bankruptcy forecasting on a balanced dataset was 60%. The simplified expert approach selected 76% of bankrupt entities, but significantly overstated the set of companies exposed on bankruptcy. Machine learning methods are effective for large data sets that are too numerous for human analysis.
Źródło:
Studia Ekonomiczne; 2018, 358; 173-181
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The prediction of myocardial infarction consequences as a result of vectorcardiography research using 'Decision trees' data mining algorithm
Prognozirovanie izkhodov infarcta miokarda po rezul'tatam vektorkardiograficheskogo issledovanija pri pomoshhi algoritma data mining 'Derevo reshenijj'
Autorzy:
Musayeva, E.
Belaya, I.
Powiązania:
https://bibliotekanauki.pl/articles/792335.pdf
Data publikacji:
2012
Wydawca:
Komisja Motoryzacji i Energetyki Rolnictwa
Tematy:
vectorcardiography
decision tree
data mining
myocardial infarction
coronary heart disease
algorithm
prediction
Źródło:
Teka Komisji Motoryzacji i Energetyki Rolnictwa; 2012, 12, 4
1641-7739
Pojawia się w:
Teka Komisji Motoryzacji i Energetyki Rolnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dobór maszyny z wykorzystaniem drzewa decyzyjnego i metody AHP
The selection on the machine with the use of decision tree and AHP methods
Autorzy:
Pacana, A.
Siwiec, D.
Powiązania:
https://bibliotekanauki.pl/articles/322976.pdf
Data publikacji:
2018
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
metoda AHP
drzewo decyzyjne
wybór najlepszej decyzji
AHP method
decision tree
choosing the best decision
Opis:
Organizacje często borykają się z problemem podjęcia decyzji w warunkach niepewności. Podjęcie ostatecznej, a tym samym najlepszej z możliwych decyzji jest bardzo trudne i przysparza przedsiębiorstwom wiele problemów, szczególnie w momencie gdy w grę wchodzi analiza kilku kryteriów problemu. Aby wspomóc proces podejmowania decyzji można posłużyć się metodą AHP (ang. Analytic Hierarchy Process), dzięki której dokonuje się wielokryterialnych analiz decyzyjnych. W artykule dokonano analizy rozwiązania problemu doboru maszyny z wykorzystaniem metody AHP. Dodatkowo dokonano analizy wystąpienia ryzyka niezgodnego wyrobu z pomocą narzędzia zarządzania jakością, jakim jest drzewo decyzyjne. Opracowana analiza i osiągnięte po niej wnioski pozwoliły na podjęcie ostatecznej decyzji o zakupie jednej z trzech maszyn grawerujących.
Organizations often have problems making decisions in conditions of uncertainty. The final and, therefore, the best decisions is very difficult and gives enterprises many problems. Making a decision is more difficult when it comes to analyzing several criteria of problem. To help the decision-making process, the AHP method (Analytic Hierarchy Process) can be used, thanks to which multicriteria decision-making analyzes are carried out. The article analyzes the solution to the problem of making decision choosing the machine using the AHP method. In addition, an analysis of the occurrence of non-compliant product risk was made with the help of the quality management tool, which is the decision tree. The analysis and the conclusions obtained after analysis allowed for the take final decision to purchase one of the three engraving machines.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2018, 131; 431-439
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of selected data mining techniques in unintentional accounting error detection
Autorzy:
Papík, Mário
Papíková, Lenka
Powiązania:
https://bibliotekanauki.pl/articles/22444352.pdf
Data publikacji:
2021
Wydawca:
Instytut Badań Gospodarczych
Tematy:
financial fraud
unintentional accounting errors
financial restatements
decision tree
classification and regression tree
random forest
Opis:
Research background: Even though unintentional accounting errors leading to financial restatements look like less serious distortion of publicly available information, it has been shown that financial restatements impacts on financial markets are similar to intentional fraudulent activities. Unintentional accounting errors leading to financial restatements then affect value of company shares in the short run which negatively impacts all shareholders. Purpose of the article: The aim of this manuscript is to predict unintentional accounting errors leading to financial restatements based on information from financial statements of companies. The manuscript analysis if financial statements include sufficient information which would allow detection of unintentional accounting errors. Methods: Method of classification and regression trees (decision tree) and random forest have been used in this manuscript to fulfill the aim of this manuscript. Data sample has consisted of 400 items from financial statements of 80 selected international companies. The results of developed prediction models have been compared and explained based on their accuracy, sensitivity, specificity, precision and F1 score. Statistical relationship among variables has been tested by correlation analysis. Differences between the group of companies with and without unintentional accounting error have been tested by means of Kruskal-Wallis test. Differences among the models have been tested by Levene and T-tests. Findings & value added: The results of the analysis have provided evidence that it is possible to detect unintentional accounting errors with high levels of accuracy based on financial ratios (rather than the Beneish variables) and by application of random forest method (rather than classification and regression tree method).
Źródło:
Equilibrium. Quarterly Journal of Economics and Economic Policy; 2021, 16, 1; 185-201
1689-765X
2353-3293
Pojawia się w:
Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-criteria decision making in project environment using decision trees and real options – a comparison of methods
Wielokryterialne decyzje w projektowaniu środowiskowym wykorzystujące drzewa decyzyjne i opcje realne – porównanie metod
Autorzy:
Nowak, Maciej
Targiel, Krzysztof S.
Powiązania:
https://bibliotekanauki.pl/articles/590071.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Decision tree
Multiple criteria decision making
Real option
Drzewo decyzyjne
Opcja realna
Podejmowanie decyzji wielokryterialnych
Opis:
The complexity of modern projects makes the proper management crucial. The volatile environment of the XXI century means that it is important to choose the right decision at the right moment. During the life of project there is the need to make many decisions, which are embedded in time. Moreover, in many cases evaluation of these decisions depends on multiple criteria. Two approaches are poposed to deal with such situation: Multicriteria Decision Tree and Multi-State Real Options (MSRO). The paper compares areas of applicability, limitations and advantages of these methods. As result, it is concluded, that MSRO method is more specific and can be used only in situations where exist real options.
Złożoność nowoczesnych projektów sprawia, że zarządzanie ma kluczowe znaczenie. Niestabilne środowisko XXI w. oznacza, że ważne jest, aby podjąć właściwą decyzję w odpowiednim momencie. W trakcie realizacji projektu konieczne jest podjęcie wielu decyzji osadzonych w czasie. Ponadto często ocena tych decyzji zależy od wielu kryteriów. W celu rozwiązania takich sytuacji pojawiają się dwa podejścia: wielokryterialne drzewo decyzyjne i wielostanowe opcje realne (MSRO). W pracy porównano obszary zastosowań, ograniczenia i zalety tych metod. W rezultacie stwierdzono, że metoda MSRO jest bardziej specyficzna i może być stosowana tylko w sytuacjach, w których istnieją opcje realne.
Źródło:
Studia Ekonomiczne; 2017, 323; 98-106
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data mining techniques as a tool in neurological disorders diagnosis
Autorzy:
Zdrodowska, M.
Dardzińska, A.
Chorąży, M.
Kułakowska, A.
Powiązania:
https://bibliotekanauki.pl/articles/386474.pdf
Data publikacji:
2018
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
data mining
classification rules
decision tree
action rules
neurological disorders
stroke
multiple sclerosis
Opis:
Neurological disorders are diseases of the brain, spine and the nerves that connect them. There are more than 600 diseases of the nervous system, such as epilepsy, Parkinson's disease, brain tumors, and stroke as well as less familiar ones such as multiple sclerosis or frontotemporal dementia. The increasing capabilities of neurotechnologies are generating massive volumes of complex data at a rapid pace. Evaluating and diagnosing disorders of the nervous system is a complicated and complex task. Many of the same or similar symptoms happen in different combinations among the different disorders. This paper provides a survey of developed selected data mining methods in the area of neurological diseases diagnosis. This review will help experts to gain an understanding of how data mining techniques can assist them in neurological diseases diagnosis and patients treatment.
Źródło:
Acta Mechanica et Automatica; 2018, 12, 3; 217-220
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
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