"785 ; 790" . "Austrian Society for Cybernetics Studies" . "Nen\u00ED k dispozici"@cs . "RIV/68407700:21230/06:03118982" . "21230" . "RIV/68407700:21230/06:03118982!RIV07-AV0-21230___" . "Visualization of Some Relational Patterns for DM"@en . . . "Nov\u00E1kov\u00E1, Lenka" . "Visualization of Some Relational Patterns for DM" . "506193" . "2006-04-18+02:00"^^ . . . "Cybernetics and Systems 2006" . "6"^^ . . "\u0160t\u011Bp\u00E1nkov\u00E1, Olga" . . . "Nen\u00ED k dispozici"@cs . "Visualization of Some Relational Patterns for DM"@en . "[B88728084111]" . "3-85206-172-5" . "data mining; visualization"@en . . . . . "P(1ET101210513)" . "We review specific properties of RadViz visualization method and its new modification RadVizS which seem to be useful to depict some relational dependencies among the studied datasets that lurk other visualization approaches. First, we demonstrate this claim using several artificial examples - here, we apply RadViz to identify interesting clusters in the multidimensional data. Encouraged by this success, we suggest an eficient RadViz-based procedure which can indicate existence of some dependencies present in a dataset described by 4-7 attributes. Obtaining such an information would not be only an important result of the data understanding phase of the data mining process. It can be a decisive step from the point of view of the data mining task as such since it can motivate introduction of some new derived attributes necessary for certain decisions."@en . "Nen\u00ED k dispozici"@cs . . "Visualization of Some Relational Patterns for DM" . "We review specific properties of RadViz visualization method and its new modification RadVizS which seem to be useful to depict some relational dependencies among the studied datasets that lurk other visualization approaches. First, we demonstrate this claim using several artificial examples - here, we apply RadViz to identify interesting clusters in the multidimensional data. Encouraged by this success, we suggest an eficient RadViz-based procedure which can indicate existence of some dependencies present in a dataset described by 4-7 attributes. Obtaining such an information would not be only an important result of the data understanding phase of the data mining process. It can be a decisive step from the point of view of the data mining task as such since it can motivate introduction of some new derived attributes necessary for certain decisions." . . . "2"^^ . . . "Vienna" . "2"^^ . "Vienna" .