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    Wyświetlanie 1-7 z 7
    Tytuł:
    Numerical Coding of Nominal Data
    Autorzy:
    Gniazdowski, Z.
    Grabowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/91423.pdf
    Data publikacji:
    2015
    Wydawca:
    Warszawska Wyższa Szkoła Informatyki
    Tematy:
    nominal data
    numerical data
    classification
    Opis:
    In this paper, a novel approach for coding nominal data is proposed. For the given nominal data, a rank in a form of complex number is assigned. The proposed method does not lose any information about the attribute and brings other properties previously unknown. The approach based on these knew properties can been used for classification. The analyzed example shows that classification with the use of coded nominal data or both numerical as well as coded nominal data is more effective than the classification, which uses only numerical data.
    Źródło:
    Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2015, 9, 12; 53-61
    1896-396X
    2082-8349
    Pojawia się w:
    Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the Analysis of Correlation Between Nominal Data and Numerical Data
    Autorzy:
    Gniazdowski, Zenon
    Powiązania:
    https://bibliotekanauki.pl/articles/2163406.pdf
    Data publikacji:
    2022-12
    Wydawca:
    Warszawska Wyższa Szkoła Informatyki
    Tematy:
    nominal data
    numerical data
    numerical coding of nominal data
    complex random variable
    correlation coefficient
    complex correlation
    complex least squares method
    Opis:
    The article investigates the possibility of measuring the strength of a linear correlation relationship between nominal data and numerical data. Correlation coefficients for variables coded with real numbers as well as for variables coded with complex numbers were studied. For variables coded with real numbers, unambiguous measures of real linear correlation were obtained. In the case of complex coding, it has been observed that the obtained complex correlation coefficients change with the permutation of the phases in the complex numbers used to code classes of elements with equal cardinalities. It was found that a necessary condition for linear correlation is the possibility of linear ordering of a set with data. Since linear order is not possible in the set of complex numbers, complex correlation coefficients cannot be used as a measure of linear correlation. In the event of such a situation, a substitute action was suggested that would prevent equal cardinality of classes of identical elements contained in the set with nominal data. This action would consist in the correction of data, analogous to the correction during preprocessing or cleaning of data containing missing or outlier values.
    Źródło:
    Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2022, 16, 27; 57-82
    1896-396X
    2082-8349
    Pojawia się w:
    Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
    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
    Tytuł:
    Independence Analysis of Nominal Data with the Use of Log-Linear Models in R
    Autorzy:
    Brzezińska, Justyna
    Powiązania:
    https://bibliotekanauki.pl/articles/465735.pdf
    Data publikacji:
    2012
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    Log-linear models
    cross-tabulation
    qualitative data
    independence analysis of nominal data
    Opis:
    Log-linear models are used to analyze the relationship between two or more categorical (e.g. nominal or ordinal) variables. The term log-linear derives from the fact that one can, through logarithmic transformations, restate the problem of analyzing multi-way frequency tables in terms that are very similar to ANOVA. Specifically, one may think of the multi-way frequency table to reflect various main effects and interaction effects that add together in a linear fashion to bring about the observed table of frequencies. There are several types of models between dependence and independence: homogenous association, partial association, conditional association and null model. Expected cell frequencies are obtained with the use of iterative proportional fitting algorithm (IPF) [Deming, Stephen 1940]. The next step is to derive model coefficients for single variables as well as for interaction parameter and the most useful tool for interpreting model parameter is odds and odds ratio. Log-linear models are available in R software with the use of loglm function in MASS library and glm function in stats library. In this paper log-linear analysis will be presented with the use of available packages on empirical datasets in economic area.
    Źródło:
    Statistics in Transition new series; 2012, 13, 2; 311-320
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Construction of the Measurement Scale for Consumer’s Attitudes in the Frame of One-Parametric Rasch Model
    Konstrukcja skali pomiaru postaw konsumenckich w ujęciu jednoparametrycznego modelu Rascha i danych dychotomicznych
    Autorzy:
    Tarka, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/904523.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
    Tematy:
    scale
    Rasch model
    the nominal – dichotomous data
    Opis:
    The article discusses issues concerning the scale design based on one-parametric Rasch model in the context of consumers’ attitudes. The first part describes the specificity of the measurement in the light of Item Response Theory (IRT). In particular the attention is paid to the nature of the dichotomous data used in the model. At last, the author presents the scale in reference to attitudes of people towards their hedonistic, consumer lifestyle.
    W artykule autor omawia zagadnienia dotyczące konstrukcji skali pomiarowej postaw konsumenckich w kontekście jednoparametrycznego modelu Rascha. W pierwszej części opisano specyfikę pomiaru w świetle teorii reakcji na odpowiedzi (IRT) oraz założenia teoretyczne stanowiące podbudowę konstrukcji skal pomiarowych. Szczególną uwagę zwrócono na charakter danych dychotomicznych. W końcowej części opracowania zaprezentowano problem badawczy w sferze konstrukcji skali do analizy postaw konsumentów wobec konsumpcyjno-hedonistycznego stylu życia. W pomiarze wykorzystano jednoparametryczny model Rascha.
    Źródło:
    Acta Universitatis Lodziensis. Folia Oeconomica; 2013, 286
    0208-6018
    2353-7663
    Pojawia się w:
    Acta Universitatis Lodziensis. Folia Oeconomica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Visualisation of nominal data – practical and theoretical remarks
    Wizualizacja danych mierzonych na skali nominalnej – uwagi praktyczne i teoretyczne
    Autorzy:
    Mącik, Radosław
    Powiązania:
    https://bibliotekanauki.pl/articles/424833.pdf
    Data publikacji:
    2016
    Wydawca:
    Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
    Tematy:
    Text data
    nominal data
    visualisation
    word cloud
    word tree
    chord graph
    correspondence analysis
    Opis:
    Nominal data, due to their nature, are often analysed statistically in a quite limited and traditional way. Usually they come from open-ended or simple/multiple choice questions. In typical research projects, such data are often presented in the form of more or less complex tables (including contingency tables) and standard charts. The author’s experience shows that such a visualisation is perceived as boring, especially by younger people, accustomed to the presentation of content in the form of infographics. The article presents examples of data analysis and a visualisation of the nominal data based on the results of the author’s research, including theoretical reflections on the techniques and tools used. The starting point is the raw text data from the responses to the open-ended questions subjected to analyses of the frequency of words and expressions, including its visualisation through word clouds. The next step is categorization and tabulation at the level of individual variables including the visualisation of categories, to assess the contingency between two nominal variables (or the nominal and the ordinal one), including visualising the relationships via chord diagrams and the correspondence analysis.
    Źródło:
    Econometrics. Ekonometria. Advances in Applied Data Analytics; 2016, 2 (52); 22-34
    1507-3866
    Pojawia się w:
    Econometrics. Ekonometria. Advances in Applied Data Analytics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The effect of binary data transformation in categorical data clustering
    Autorzy:
    Cibulková, Jana
    Šulc, Zdenek
    Sirota, Sergej
    Rezanková, Hana
    Powiązania:
    https://bibliotekanauki.pl/articles/1194463.pdf
    Data publikacji:
    2019-07-02
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    hierarchical cluster analysis
    nominal variable
    binary variable
    categorical data
    similarity measures
    evaluation criteria
    generated data
    Opis:
    This paper focuses on hierarchical clustering of categorical data and compares two approaches which can be used for this task. The first one, an extremely common approach, is to perform a binary transformation of the categorical variables into sets of dummy variables and then use the similarity measures suited for binary data. These similarity measures are well examined, and they occur in both commercial and non-commercial software. However, a binary transformation can possibly cause a loss of information in the data or decrease the speed of the computations. The second approach uses similarity measures developed for the categorical data. But these measures are not so well examined as the binary ones and they are not implemented in commercial software. The comparison of these two approaches is performed on generated data sets with categorical variables and the evaluation is done using both the internal and the external evaluation criteria. The purpose of this paper is to show that the binary transformation is not necessary in the process of clustering categorical data since the second approach leads to at least comparably good clustering results as the first approach.
    Źródło:
    Statistics in Transition new series; 2019, 20, 2; 33-47
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-7 z 7

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