A set of manipulated and unmanipulated pairwise comparison matrices
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https://agh.rodbuk.pl/citation?persistentId=doi:10.58032/AGH/E8LV5J
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A distinct set of the training data was generated for each of the tested size of the PC matrix C. Each set consists of three distinct *.json files, which are used to train and test the neural networks designed to detect one of the three described attack algorithms (naive, basic, advanced). The previously mentioned *.json files have the same name as the algorithm they are used to test (e.g. basic.json), and are placed in a folder whose name determines the size (n) of the matrix C and the number of independent data samples for each of the tested algorithms (e.g. data_7_7_10000). Each of the data sample is structured as follows: • id - index of the sample • CI - Saaty's consistency ratio of PC matrix C • matrix - generated PC matrix C • errorMatrix - error matrix calculated for matrix • koczkodajInconsistencyMatrix - modified Koczkodaj's inconsistency matrix calculated for matrix • determinantMatrix - determinant matrix (12) calculated for matrix • distrurbedCI - Saaty's consistency ratio of modified PC matrix C' • distrurbedMatrix - modified (because of the carried out attack) PC matrix C' • distrurbedErrorMatrix - determinant matrix (12) calculated for disturbedMatrix • distrurbedKoczkodajInconsistencyMatrix - modified Koczkodaj's inconsistency matrix calculated for disturbedMatrix • distrurbedDeterminantMatrix - Analogously to determinantMatrix, but calculated for disturbedMatrix Some of that fields are not used in the experiments (e.g. koczkodajInconsistencyMatrix) but we think that they may prove useful in future studies.
提供机构:
AGH University of Krakow
创建时间:
2024-05-22



