Temat: Rough sets - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Hardware rough set processor parallel architecture in FPGA for finding core in big datasets
Autorzy:: Kopczyński, Maciej
Grześ, Tomasz
Powiązania:: https://bibliotekanauki.pl/articles/2031135.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: rough sets
FPGA
core attributes
parallel architecture
Opis:: This paper presents FPGA and softcore CPU based solution for large datasets parallel core calculation using rough set methods. Architectures shown in this paper have been tested on two real datasets running presented solutions inside FPGA unit. Tested datasets had 1 000 to 10 000 000 objects. The same operations were performed in software implementation. Obtained results show the big acceleration in computation time using hardware supporting core generation in comparison to pure software implementation.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 2; 99-110
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Performance analysis of rough set–based hybrid classification systems in the case of missing values
Autorzy:: Nowicki, Robert K.
Seliga, Robert
Żelasko, Dariusz
Hayashi, Yoichi
Powiązania:: https://bibliotekanauki.pl/articles/2031102.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: rough sets
support vector machine
fuzzy system
neural networks
Opis:: The paper presents a performance analysis of a selected few rough set–based classification systems. They are hybrid solutions designed to process information with missing values. Rough set-–based classification systems combine various classification methods, such as support vector machines, k–nearest neighbour, fuzzy systems, and neural networks with the rough set theory. When all input values take the form of real numbers, and they are available, the structure of the classifier returns to a non–rough set version. The performance of the four systems has been analysed based on the classification results obtained for benchmark databases downloaded from the machine learning repository of the University of California at Irvine.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 307-318
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Rough support vector machine for classification with interval and incomplete data
Autorzy:: Nowicki, Robert K.
Grzanek, Konrad
Hayashi, Yoichi
Powiązania:: https://bibliotekanauki.pl/articles/91559.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: support vector machines
rough sets
missing features
interval data
three–way decision
maszyna wektorów nośnych
dane interwałowe
Opis:: The paper presents the idea of connecting the concepts of the Vapnik’s support vector machine with Pawlak’s rough sets in one classification scheme. The hybrid system will be applied to classifying data in the form of intervals and with missing values [1]. Both situations will be treated as a cause of dividing input space into equivalence classes. Then, the SVM procedure will lead to a classification of input data into rough sets of the desired classes, i.e. to their positive, boundary or negative regions. Such a form of answer is also called a three–way decision. The proposed solution will be tested using several popular benchmarks.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 47-56
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

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