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Tytuł:
Informational database on selected music works
Autorzy:
Hippe, M. P.
Powiązania:
https://bibliotekanauki.pl/articles/1941711.pdf
Data publikacji:
2000
Wydawca:
Politechnika Gdańska
Tematy:
attribute of music
decision trees
inference rules
Opis:
Basing on the review of available literature devoted to applications of programming tools in research on mechanism of music perception, the first results of my own research devoted to mining of hidden regularities in pieces of various types of music is presented. General characteristics of the developed databases, methodology of executed research, and discussion of the discovered knowledge structures for selected types of music pieces are briefly dealt with.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2000, 4, 1; 83-90
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using Decision Trees to Evaluate Courier Companies from the Perspective of Online Retailers
Autorzy:
Kulińska, Ewa
Wojtynek, Lilianna
Dendera-Gruszka, Małgorzata
Flauder, Sandra
Powiązania:
https://bibliotekanauki.pl/articles/503776.pdf
Data publikacji:
2017
Wydawca:
Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:
decision-making process
decision trees
service companies
online sales
Opis:
The analysis of the research problem started from listing the issues of decision theory and the decision-making process that support the process of building decision trees. The area in question covers a procedure for building and proceeding when creating decision trees. The solution to the research problem consists in defining decision variables and arranging them into logical statements by writing down all possible variants and only accounting for the true ones. True solutions derived from coding were detailed and the number of occurring decision trees was calculated in the case under consideration. The decision problem was presented in the form of decision trees, which made it possible to select the optimum decision tree. The obtained results were considered and the optimum decision tree was chosen. At the same time, the record of decision variables was analyzed, providing the answer as to which courier company will best meet expectations of entrepreneurs and ensure the most satisfying cooperation. That company turned out to be K-EX. The article aimed to select a courier company from the perspective of online retailers, with the selection having been made using the method of decision trees based on four basic criteria defined within the research.
Źródło:
Logistics and Transport; 2017, 35, 3; 59-66
1734-2015
Pojawia się w:
Logistics and Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Uplift Modeling in Direct Marketing
Autorzy:
Rzepakowski, P.
Jaroszewicz, S.
Powiązania:
https://bibliotekanauki.pl/articles/309211.pdf
Data publikacji:
2012
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
decision trees
information theory
marketing tools
uplift modeling
Opis:
Marketing campaigns directed to randomly selected customers often generate huge costs and a weak response. Moreover, such campaigns tend to unnecessarily annoy customers and make them less likely to answer to future communications. Precise targeting of marketing actions can potentially results in a greater return on investment. Usually, response models are used to select good targets. They aim at achieving high prediction accuracy for the probability of purchase based on a sample of customers, to whom a pilot campaign has been sent. However, to separate the impact of the action from other stimuli and spontaneous purchases we should model not the response probabilities themselves, but instead, the change in those probabilities caused by the action. The problem of predicting this change is known as uplift modeling, differential response analysis, or true lift modeling. In this work, tree-based classifiers designed for uplift modeling are applied to real marketing data and compared with traditional response models, and other uplift modeling techniques described in literature. The experiments show that the proposed approaches outperform existing uplift modeling algorithms and demonstrate significant advantages of uplift modeling over traditional, response based targeting.
Źródło:
Journal of Telecommunications and Information Technology; 2012, 2; 43-50
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie logicznych drzew decyzyjnych do analizy wad w etapie lutowania na fali podczas montażu SMT
Application of logical decision trees to analysis of defects at the stage of wave soldering during the SMT process
Autorzy:
Sadowińska, M.
Powiązania:
https://bibliotekanauki.pl/articles/340136.pdf
Data publikacji:
2014
Wydawca:
Polskie Towarzystwo Zarządzania Produkcją
Tematy:
proces SMT
lutowanie na fali
drzewo decyzyjne
logiczne drzewa decyzyjne
SMT process
wave soldering
decision trees
logical decision trees
Opis:
Decision trees are a logical method, which graphically presents the solution of logical function. They consist of the branch on which the data are coded variables. Solutions are presented as the true path. The method used to optimize the solution functions are logical decision trees, the construction of which the principle is the same as the logical trees. They make it possible to eliminate the occurrence of twigs isolated and cut off the full beam. This procedure allows to minimize the real twigs. This is advantageous due to the phenomenon that the optimal solution is the combination of variables, which is associated with the tree having the smallest number of real branches. This tree defines the status of the variables tested from most to least important. The purpose of the study was to determine the hierarchy of defects affecting the destabilization of one of the stages of the process SMT (surface mount), which is the wave soldering, and by this determine which should be eliminated in the first place. A tool that has been used for this purpose was a logical decision trees. According to the results of the analysis in the first place should prevent the causes of the formation of solder bridges (machine failure), then-without regard to the order-of overheating the PCB and too low solder temperature (the same effects on the occurrence of errors), which are the result of poor machine settings and the occurrence of machine failure. Thanks to the possibility of using minimization of logical variables (cutting off the full beam) in practical terms, the elimination of identified defects, it is necessary to determine the corrective action regarding the causes of defects, namely the lack of solder. This approach meant that the error should not be the subject of corrective action performed. The indicating reason was responsible only for the occurrence of the lack of solder. The using of logical decision trees could help identify priorities for improvements to the wave soldering realized as part of a process of SMT assembly.
Źródło:
Zarządzanie Przedsiębiorstwem; 2014, 17, 2; 26-33
1643-4773
Pojawia się w:
Zarządzanie Przedsiębiorstwem
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The number of clusters in hybrid predictive models: does it really matter?
Autorzy:
Łapczyński, Mariusz
Jefmański, Bartłomiej
Powiązania:
https://bibliotekanauki.pl/articles/1046637.pdf
Data publikacji:
2020
Wydawca:
Główny Urząd Statystyczny
Tematy:
hybrid predictive model
k-means algorithm
decision trees
Opis:
For quite a long time, research studies have attempted to combine various analytical tools to build predictive models. It is possible to combine tools of the same type (ensemble models, committees) or tools of different types (hybrid models). Hybrid models are used in such areas as customer relationship management (CRM), web usage mining, medical sciences, petroleum geology and anomaly detection in computer networks. Our hybrid model was created as a sequential combination of a cluster analysis and decision trees. In the first step of the procedure, objects were grouped into clusters using the k-means algorithm. The second step involved building a decision tree model with a new independent variable that indicated which cluster the objects belonged to. The analysis was based on 14 data sets collected from publicly accessible repositories. The performance of the models was assessed with the use of measures derived from the confusion matrix, including the accuracy, precision, recall, F-measure, and the lift in the first and second decile. We tried to find a relationship between the number of clusters and the quality of hybrid predictive models. According to our knowledge, similar studies have not been conducted yet. Our research demonstrates that in some cases building hybrid models can improve the performance of predictive models. It turned out that the models with the highest performance measures require building a relatively large number of clusters (from 9 to 15).
Źródło:
Przegląd Statystyczny; 2019, 66, 3; 228-238
0033-2372
Pojawia się w:
Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new algorithm for generation of decision trees
Autorzy:
Grzymała-Busse, J. W.
Hippe, Z. S.
Knap, M.
Mroczek, T.
Powiązania:
https://bibliotekanauki.pl/articles/1965778.pdf
Data publikacji:
2004
Wydawca:
Politechnika Gdańska
Tematy:
artificial intelligence
supervised machine learning
decision trees
Bayes networks
Opis:
A new algorithm for development of quasi-optimal decision trees, based on the Bayes theorem, has been created and tested. The algorithm generates a decision tree on the basis of Bayesian belief networks, created prior to the formation of the decision tree. The efficiency of this new algorithm was compared with three other known algorithms used to develop decision trees. The data set used for the experiments was a set of cases of skin lesions, histopatolgically verified.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2004, 8, 2; 243-247
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Active learning using pessimistic expectation estimators
Autorzy:
Rokach, L.
Naamani, L.
Shmilovici, A.
Powiązania:
https://bibliotekanauki.pl/articles/970816.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
cost-sensitive learning
active learning
direct marketing
decision trees
Opis:
Active learning is the process in which unlabeled instances are dynamically selected for expert labelling, and then a classifier is trained on the labeled data. Active learning is particularly useful when there is a large set of unlabeled instances, and acquiring a label is costly. In business scenarios such as direct marketing, active learning can be used to indicate which customer to approach such that the potential benefit from the approached customer can cover the cost of approach. This paper presents a new algorithm for cost-sensitive active learning using a conditional expectation estimator. The new estimator focuses on acquisitions that are likely to improve the profit. Moreover, we investigate simulated annealing techniques to combine exploration with exploitation in the classifier construction. Using five evaluation metrics, we evaluated the algorithm on four benchmark datasets. The results demonstrate the superiority of the proposed method compared to other algorithms.
Źródło:
Control and Cybernetics; 2009, 38, 1; 261-280
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine fault diagnosis and condition prognosis using classification and regression trees and neuro-fuzzy inference systems
Autorzy:
Tran, V. T.
Yang, B. S.
Powiązania:
https://bibliotekanauki.pl/articles/971018.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
fault diagnosis
classification
induction motors
decision trees
forecasts
fuzzy systems
Opis:
This paper presents an approach to machine fault diagnosis and condition prognosis based on classification and regression trees (CART) and neuro-fuzzy inference systems (ANFIS). In case of diagnosis, CART is used as a feature selection tool to select pertinent features from data set, while ANFIS is used as a classifier. The crisp rules obtained from CART are then converted to fuzzy if-then rules, employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. The data sets obtained from vibration signals and current signals of the induction motors are used to evaluate the proposed algorithm. In case of prognosis, both of these models in association with direct prediction strategy for long-term prediction of time series techniques are utilized to forecast the future values of machine operating condition. In this case, the number of available observations and the number of predicted steps are initially determined by false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models. The performance of the proposed prognosis system is then evaluated by using real trending data of a low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results of the proposed methods in both cases indicate that CART and ANFIS offer a potential for machine fault diagnosis and for condition prognosis.
Źródło:
Control and Cybernetics; 2010, 39, 1; 25-55
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Identification of radon anomalies in soil gas using decision trees and neural networks
Autorzy:
Zmazek, B.
Džeroski, S.
Torkar, D.
Vaupotič, J.
Kobal, I.
Powiązania:
https://bibliotekanauki.pl/articles/148699.pdf
Data publikacji:
2010
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
radon
soil gas
anomalies
decision trees
artificial neural network
earthquakes
Opis:
The time series of radon (222Rn) concentration in soil gas at a fault, together with the environmental parameters, have been analysed applying two machine learning techniques: (i) decision trees and (ii) neural networks, with the aim at identifying radon anomalies caused by seismic events and not simply ascribed to the effect of the environmental parameters. By applying neural networks, 10 radon anomalies were observed for 12 earthquakes, while with decision trees, the anomaly was found for every earthquake, but, undesirably, some anomalies appeared also during periods without earthquakes.
Źródło:
Nukleonika; 2010, 55, 4; 501-505
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Generowanie wielowymiarowych drzew decyzyjnych na podstawie zbiorów danych
Induction of multivariate decision trees from datasets
Autorzy:
Krętowski, M.
Bobrowski, L.
Powiązania:
https://bibliotekanauki.pl/articles/341161.pdf
Data publikacji:
2002
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
kryteria dipolowe
wielowymiarowe drzewa decyzyjne
dipoler criteria
multivariate decision trees
Opis:
W pracy przedstawiono nowe metody konstruowania klasyfikatorów o postaci wielowymiarowych (skośnych) drzew decyzyjnych na podstawie zbiorów uczących. Generowane drzewa zawierają w każdym węźle liniową regułę decyzyjną (hiperpłaszczyznę), która dzieli wektory cech docierające do tego węzła na dwa podzbiory. Strategie poszukiwania hiperpłaszczyzny decyzyjnej opierają się na minimalizacji dipolowych funkcji kryterialnych, a jako procedury optymalizujące wykorzystywane są algorytmy wymiany rozwiązań bazowych lub algorytmy ewolucyjne. Aby wyeliminować nadmiarowe cechy, w proces poszukiwania optymalnej kombinacji liniowej w węźle wbudowana została selekcja cech. Dla uniknięcia zbytniego dopasowania do danych treningowych i zwiększenia zdolności do generalizacji, uzyskane drzewo jest przycinane. Przedstawione metody zostały zweryfikowane eksperymentalnie na publicznie dostępnych zbiorach danych i porównane z innymi algorytmami indukującymi drzewa decyzyjne.
In the paper, new methods for induction of classifiers in the form of multivariate (oblique) decision trees are presented. A linear decision function is used at each non-terminal node of the binary tree for splitting the data. The strategies for finding the decision hyper-plane are based on the concept of dipoles and as optimization procedures they use evolutionary algorithms or basis exchange algorithms. To eliminate redundant and noisy features we embedded into the process of searching for the optimal linear combination in each node the feature selection mechanism. To avoid over-fitting and to increase generalization the tree is pruned back after the growing phase. The presented methods were experimentally verified on publicly available datasets and compared with other decision tree systems.
Źródło:
Zeszyty Naukowe Politechniki Białostockiej. Informatyka; 2002, Z.1; 119-146
1644-0331
Pojawia się w:
Zeszyty Naukowe Politechniki Białostockiej. Informatyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation of the Utility of Using Classification Algorithms when Designing New Polymer Composites
Autorzy:
Dębska, Bernardeta
Dębska, Barbara
Lichołai, Lech
Powiązania:
https://bibliotekanauki.pl/articles/123424.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
polymer mortars
waste materials
polyethylene terephthalate
discriminant analysis
decision trees
Opis:
Polymer composites are the materials that can be successfully used in the places where high mechanical strength and chemical resistance as well as low absorbability are required. These unique features of polymer composites are obtained mainly due to a suitably selected binder, i.e. a synthetic resin. At the same time, this component accounts for the high production costs of these materials. Partial substitution of the resin with glycolisates obtained using poly(ethylene terephthalate) waste (PET), helps reduce the price of polymeric mortars, while maintaining favourable physicomechanical properties. This modification method also has a beneficial effect on the environment, as it allows the utilisation of a very common waste, which is difficult to dispose of. The article concerns three types of resin mortars, i.e. epoxy, polyester and polyester with the addition of colloidal silica, modified with PET glycolisate. On the basis of the obtained data set and database knowledge mining techniques, such as discriminant analysis and decision trees, it was shown to what extent the type of resin and the presence of an added modifier differentiate the mortar properties. The results obtained with both methods were compared. It was confirmed that these techniques are effective both in the classification and prediction of the type (selection) of mortar in the process of designing new composites.
Źródło:
Journal of Ecological Engineering; 2019, 20, 8; 212-225
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Early detection of bearing damage by means of decision trees
Autorzy:
Kilundu, B.
Dehombreux, P.
Letot, Ch.
Chiementin, X.
Powiązania:
https://bibliotekanauki.pl/articles/384675.pdf
Data publikacji:
2009
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
damage detection
bearing damage
envelope detection
decision trees
preventive maintenance
Opis:
This paper presents a procedure for early detection of rolling bearing damages on the basis of vibration measurements. First, an envelope analysis is performed on bandpass filtered signals. For each frequency range, a feature indicator is defined as sum of spectral lines. These features are passed through a principal component model to generate a single variable, which allows tracking change in the bearing health. Thresholds and rules for early detection are learned thanks to decision trees. Experimental results demonstrate that this procedure enables early detection of bearing defects.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2009, 3, 3; 70-74
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza drzew decyzyjnych na gruncie teorii perspektywy
Decision tree analysis based on prospect theory
Autorzy:
Dudzińska-Baryła, R.
Powiązania:
https://bibliotekanauki.pl/articles/327072.pdf
Data publikacji:
2017
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
drzewa decyzyjne
kumulacyjna teoria perspektywy
decision trees
cumulative prospect theory
Opis:
Powszechnie stosowaną graficzną metodą wspomagania procesu decyzyjnego w warunkach ryzyka są drzewa decyzyjne. Jako kryterium wyboru optymalnej decyzji zwykle stosuje się maksymalizację wartości oczekiwanej. W behawioralnym podejściu do analizy decyzyjnej uwzględnia się subiektywne czynniki, które często powodują, iż decyzje decydentów nie są zgodne z podejściem normatywnym. W pracy zostanie zaproponowana procedura oceny problemów decyzyjnych, które można przedstawić za pomocą drzew decyzyjnych zawierających dwa lub więcej etapów, wykorzystująca zasady kumulacyjnej teorii perspektywy.
The decision trees are a commonly used graphical method for analysis of decisions under conditions of risk. As the criterion for choosing the optimal decision the expected value criterion is usually used. In the behavioral decision analysis, subjective factors are taken into account, which often causes that the preferred decision differs from optimal decision based on the normative approach. In this paper we propose procedures for the analysis of decision problems, which can be presented by decision trees with two or more stages. These procedures are based on cumulative prospect theory.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2017, 113; 67-82
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of machine learning and rough set theory in lean maintenance decision support system development
Autorzy:
Antosz, Katarzyna
Jasiulewicz-Kaczmarek, Małgorzata
Paśko, Łukasz
Zhang, Chao
Wang, Shaoping
Powiązania:
https://bibliotekanauki.pl/articles/2038009.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
lean maintenance
availability
machine learning
decision trees
rough set theory
Opis:
Lean maintenance concept is crucial to increase the reliability and availability of maintenance equipment in the manufacturing companies. Due the elimination of losses in maintenance processes this concept reduce the number of unplanned downtime and unexpected failures, simultaneously influence a company’s operational and economic performance. Despite the widespread use of lean maintenance, there is no structured approach to support the choice of methods and tools used for the maintenance function improvement. Therefore, in this paper by using machine learning methods and rough set theory a new approach was proposed. This approach supports the decision makers in the selection of methods and tools for the effective implementation of Lean Maintenance.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 4; 695-708
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Diagnostics of the drive shaft bearing based on vibrations in the high-frequency range as a part of the vehicles self-diagnostic system
Autorzy:
Nowakowski, Tomasz
Komorski, Pawel
Powiązania:
https://bibliotekanauki.pl/articles/2057986.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
self-diagnostic system
vibration
vehicles
signal processing methods
decision trees
Opis:
Currently, one of the trends in the automotive industry is to make vehicles as autonomous as possible. In particular, this concerns the implementation of complex and innovative selfdiagnostic systems for cars. This paper proposes a new diagnostic algorithm that evaluates the performance of the drive shaft bearings of a road vehicle during use. The diagnostic parameter was selected based on vibration measurements and machine learning analysis results. The analyses included the use of more than a dozen time domain features of vibration signal in different frequency ranges. Upper limit values and down limit values of the diagnostic parameter were determined, based on which the vehicle user will receive information about impending wear and total bearing damage. Additionally, statistical verification of the developed model and validation of the results were performed.
Źródło:
Eksploatacja i Niezawodność; 2022, 24, 1; 70--79
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
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