Further, a non-mathematical overview of the statistical and computational methods that are available for the analysis and subsequent data mining of these data will be discussed, together with an outline of the
There are, however, negative social perceptions about data mining, among which potential privacy invasion and potential discrimination. The latter consists of unfairly treating people on the basis of their belonging to a specific group. In the age of Database technologies a large amount of data is...
The similarity-based data fusion methods (slide decks (opens in new tab)) The probabilistic-based data fusion methods (slide decks (opens in new tab)) Transfer learning-based data fusion methods (slide decks (opens in new tab)) Opens in a new tab © IEEE. Personal use of this materi...
data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own...
Data Science methodologies empower the representation and quantitative investigation in the field of smart healthcare. It is of extraordinary noteworthines
They enable fast, systematic analyses and can be implemented as standardised data evaluation procedures. Although EBSD and crystallographic characterisation techniques have been continuously improved over the years, further efforts in data mining are still needed to make the most of the information gained...
Impact analysis. Evaluating the potential damage in terms ofdata loss, operational disruption, financial costs, and reputational harm to the organization. Reporting Comprehensive reporting is essential to communicate the penetration test findings to stakeholders effectively. The report provides a detailed acc...
Ethics is one of the most important topics to emerge in machine learning and data mining. We ask you to think about the ethical implications of your submission such as, e.g., related to the collection and processing of personal data, the inference of personal information, or the potential ...
Impact analysis. Evaluating the potential damage in terms ofdata loss, operational disruption, financial costs, and reputational harm to the organization. Reporting Comprehensive reporting is essential to communicate the penetration test findings to stakeholders effectively. The report provides a detailed acc...
select article Comparison of inference methods for estimating semivariogram model parameters and their uncertainty: The case of small data sets Research articleAbstract only Comparison of inference methods for estimating semivariogram model parameters and their uncertainty: The case of small data sets Eulogio...