]> The name to uniquely identify an Attribut/Column in a DataTable is stored here. Esp needed for execution of operators. A categorial value should be marked as frequent, iff it is 50% more frequent than we would expect under a uniform distribution. (e.g. 75% for a binary value) A categorial value should be marked as rare, iff it is 50% less frequent than we would expect under a uniform distribution. (e.g. 25% for a binary value) A categorial value should be marked as rare, iff it is 90% more frequent than we would expect under a uniform distribution. (e.g. 95% for a binary value) A categorial value should be marked as rare, iff it is 90% less frequent than we would expect under a uniform distribution. (e.g. 5% for a binary value) 1 Data are manipulated in selected Attributes [targetColumn only CategorialColumn](?D) ->ClassificationLearner(?this) 1 http://www.e-LICO.eu/public/planGraphIcon/Data.gif 1 http://www.e-LICO.eu/public/planGraphIcon/Table.gif 1 1 Operators to read in Data tables in various formats 1 Default Data Table Reader http://elico.rapid_i.com/getRDFInstancesFromURL 1 http://www.e-LICO.eu/public/planGraphIcon/Texts.gif 1 1 http://www.e-LICO.eu/public/planGraphIcon/Images.gif 1 1 Data are manipulated in selected (queried) rows. 1 1 1 0 a Datatable were all "used" columns are mising value free. (unused columns, i.e. neither input nor target may contain missing values) http://www.e-LICO.eu/public/planGraphIcon/Model.gif 1 1 1 1 1 1 1 1 1 1 1 1 1.0 0.0 1 1 1 0 1 1 1 0 [targetColumn only ScalarColumn](?D) ->RegressionLearner(?this) http://www.e-LICO.eu/public/planGraphIcon/Report.gif 1 [DataTable and (targetAttribute exactly 1 Attribute) and (inputAttribute min 1 Attribute) and (targetColumn only (DataColumn and columnHasType only (Scalar or Categorial))) and (inputColumn only (DataColumn and columnHasType only (Scalar or Categorial))) ](?D) -> new(?this), SupervisedLearner(?this), uses(?this,?D) uses(?this,?D), SupervisedLearner(?this), inputColumn(?D,?IC), targetColumn(?D,?TC) -> copy(?M,?D,{DataTable(?D),containsColumn(?D,?_),amountOfRows(?D,?_)}), produces(?this,?M), PredictionModel(?M), needsColumn(?M,?IC), predictsColumn(?M,?TC) This "Flag" is set by an Operator that drops all columns with to many (treshold parameter) missing values. It is required by Operators that try to fill in missing values (as it is senseless to try that on to few examples) This "Flag" is set by an Operator that drops all records with to many (treshold parameter) missing values True for all DataTables without targetColumn of with targetColumns that do not contain missing values 0 1 0.0 1.0 1 1 0 1 1 1 0