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Wyświetlanie 1-3 z 3
Tytuł:
Modeling preparation for data mining processes
Autorzy:
Eule, T.
Powiązania:
https://bibliotekanauki.pl/articles/308872.pdf
Data publikacji:
2006
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
data mining
data preparation
KDD process
Opis:
Today many different software tools for decision support exist; the same is true for data mining which can be seen as a particularly challenging sub-area of decision support. Choosing the most suitable tool for a particular industrial data mining application is becoming difficult, especially for industrial decision makers whose expertise is in a different field. This paper provides a conceptual analysis of crucial features of current data mining software tools, by establishing an abstract view on typical processes in data mining. Thus a common terminology is given which simplifies the comparison of tools. Based on this analysis, objective decisions for the application of decision supporting software tools in industrial practice can be made.
Źródło:
Journal of Telecommunications and Information Technology; 2006, 4; 81-87
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Rough Set-Based Knowledge Discovery Process
Autorzy:
Zhong, N.
Skowron, A.
Powiązania:
https://bibliotekanauki.pl/articles/908370.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
baza danych
baza wiedzy
system hybrydowy
rough sets
KDD process
hybrid systems
Opis:
The knowledge discovery from real-life databases is a multi-phase process consisting of numerous steps, including attribute selection, discretization of real-valued attributes, and rule induction. In the paper, we discuss a rule discovery process that is based on rough set theory. The core of the process is a soft hybrid induction system called the Generalized Distribution Table and Rough Set System (GDT-RS) for discovering classification rules from databases with uncertain and incomplete data. The system is based on a combination of Generalization Distribution Table (GDT) and the Rough Set methodologies. In the preprocessing, two modules, i.e. Rough Sets with Heuristics (RSH) and Rough Sets with Boolean Reasoning (RSBR), are used for attribute selection and discretization of real-valued attributes, respectively. We use a slope-collapse database as an example showing how rules can be discovered from a large, real-life database.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 3; 603-619
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks
Autorzy:
Kalnoor, Gauri
Gowrishankar, -
Powiązania:
https://bibliotekanauki.pl/articles/1839336.pdf
Data publikacji:
2021
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
DDoS
intrusion detection
IoT
machine learning
Markov decision process
MDP
Q-learning
NSL-KDD
reinforcement learning
Opis:
In this paper, a new reinforcement learning intrusion detection system is developed for IoT networks incorporated with WSNs. A research is carried out and the proposed model RL-IDS plot is shown, where the detection rate is improved. The outcome shows a decrease in false alarm rates and is compared with the current methodologies. Computational analysis is performed, and then the results are compared with the current methodologies, i.e. distributed denial of service (DDoS) attack. The performance of the network is estimated based on security and other metrics.
Źródło:
Journal of Telecommunications and Information Technology; 2021, 3; 42-49
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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