/** * Returns a string describing this filter * * @return a description of the filter suitable for displaying in the * explorer/experimenter gui */ public String globalInfo() { return "Reduces the dimensionality of the data by projecting" + " it onto a lower dimensional subspace using a random" + " matrix with columns of unit length. It will reduce" + " the number of attributes in the data while preserving" + " much of its variation like PCA, but at a much less" + " computational cost.\n" + "It first applies the NominalToBinary filter to" + " convert all attributes to numeric before reducing the" + " dimension. It preserves the class attribute.\n\n" + "For more information, see:\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing this filter * * @return a description of the filter suitable for displaying in the * explorer/experimenter gui */ public String globalInfo() { return "Reduces the dimensionality of the data by projecting" + " it onto a lower dimensional subspace using a random" + " matrix with columns of unit length. It will reduce" + " the number of attributes in the data while preserving" + " much of its variation like PCA, but at a much less" + " computational cost.\n" + "It first applies the NominalToBinary filter to" + " convert all attributes to numeric before reducing the" + " dimension. It preserves the class attribute.\n\n" + "For more information, see:\n\n" + getTechnicalInformation().toString(); }