IDA - Intelligent Data Analysis Research Group

BibTeX Entry

  file = {report_GL213-10.pdf},
  category = {ida-publications},
  author = {Mat{\v e}j Holec and Filip {\v Z}elezn{\'y} and Ji{\v r}{\'i} Kl{\'e}ma and Jakub Tolar},
  title = {Comparative Evaluation of Set-Level Techniques in Predictive Classification of Gene Expression Samples},
  year = {2010},
  institution = {CTU, Faculty of  Electrical Engineering, Gerstner Laboratory, Prague},
  abstract = {In several research areas, complex experiments need to be accomplished. Data Mining experiments are very common in such areas. Usually these kind of experiments are very complex in number of tasks and amount of data to process. A way of defining and managing such experiments becomes vital in order to handle the complexity involved. In this work, a framework for the management of Data Mining experiments is presented. The framework allows the definition of experiments in two levels, the first one for the structure and the second one for particular instances of experiments according to a predefined structure. Workflows become a convenient tool for the representation of the experiments. The use of workflows facilitates to take advantage of the benefits it can provide a Grid execution environment. Estimation methods are used in order to improve the performance of experiment’s execution over the Grid.},
  vvvs = {1},
  projnum = {SGS10/071/OHK4/1T/13  201/09/1},

Creative Commons License  Content on this site is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Czech Republic License.