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Wyszukujesz frazę "Shannon theory" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Prediction of Missing Values in Adult Data Set of UCI Machine Learning : A Case of Study
Autorzy:
Luna, Alejandra
Bello, Mario
Hernandez, Ana
Bonilla, Edmundo
Powiązania:
https://bibliotekanauki.pl/articles/1397481.pdf
Data publikacji:
2020
Wydawca:
Warszawska Wyższa Szkoła Informatyki
Tematy:
Shannon theory
entropy
missing attributes
adult dataset
UCI Machine Learning
Opis:
These days, not having complete data of any kind can be a big problem for different organizations when making decisions. In this article, we propose to use Shannon entropy and information gain to predict and impute missing categorical data in any data set. It is detailed with an example of how entropy is applied and knows the level of uncertainty of each attribute value. Likewise, the imputation of the missing attributes is also carried out with other imputation techniques in the Adult data set of UCI Machine Learning to denote the advantages offered by the proposed methodology.
Źródło:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2020, 14, 22; 7-21
1896-396X
2082-8349
Pojawia się w:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Shannon-inspired information in the clinical use of neural signals concerning post-comatose patients
Autorzy:
Noh, Hyungrae
Powiązania:
https://bibliotekanauki.pl/articles/28763358.pdf
Data publikacji:
2022
Wydawca:
Copernicus Center Press
Tematy:
postcomatose disorders of consciousness
Shannon’s theory of information
minimal consciousness
mental action
Opis:
Post-comatose patients are classified as being in a minimally conscious state when they have executive functions. Because traditional behavioral assessments may not capture signs of executive functions in post-comatose patients, clinicians look to localized brain activities in response to task instructions, such as imagining wiggling toes, to diagnose minimal consciousness. This paper critically assesses the assumption underlying such alternative methods: that brain activities are neural signals conveying information about minimal consciousness. Based on a Shannon-inspired idea of information, I distinguish between informational and engineering aspects of clinical tasks. The informational aspect concerns the conditional probability that, for example, given activity in the motor areas of the brain in response to task instructions, a patient is imagining wiggling toes. The engineering aspect concerns efficient activation of the relevant brain areas in a patient under the task conditions. This distinction shows that the current alternative methods are not informationally problematic, but are structurally “ill-formed.” For instance, the toe-imagery task requires the capacity to comprehend syntactically complex sentences, which can be dissociated from minimal consciousness. I propose a misrepresentation task, which tests the capacity to misconceptualize lukewarm water as melting wax, as a supplement to the current alternative methods. This task is as informationally reliable as these methods, but is structurally “well-formed,” as it does not rely methodologically on prerequisites such as language comprehension.
Źródło:
Zagadnienia Filozoficzne w Nauce; 2022, 73; 121-145
0867-8286
2451-0602
Pojawia się w:
Zagadnienia Filozoficzne w Nauce
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimation of information entropy based on its visualization
Autorzy:
Cholewa, M.
Palys, M.
Powiązania:
https://bibliotekanauki.pl/articles/333282.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
Shannon's entropy
information theory
visualization
entropia Shannona
teoria informacji
wizualizacja
Opis:
This paper describes the method which allows an estimation of information entropy in the meaning of Shannon. The method is suitable to an estimation which sample has a higher value of information entropy. Several algorithms have been used to estimate entropy, assuming that they do it faster. Each algorithm has calculated this value for several text samples. Then analysis has verified which comparisons of the two samples were correct. It has been found that the probabilistic algorithm is the fastest and most effective in returning the estimated value of entropy.
Źródło:
Journal of Medical Informatics & Technologies; 2017, 26; 18-25
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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