/** * Returns a string describing this data generator. * * @return a description of the data generator suitable for displaying in the * explorer/experimenter gui */ public String globalInfo() { return "Generates a people database and is based on the paper by Agrawal " + "et al.:\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing the stemmer * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "A stemmer based on the Lovins stemmer, described here:\n\n" + getTechnicalInformation().toString(); }
/** * This will return a string describing the classifier. * * @return The string. */ @Override public String globalInfo() { return "This Bayes Network learning algorithm determines the maximum weight spanning tree " + " and returns a Naive Bayes network augmented with a tree.\n\n" + "For more information see:\n\n" + getTechnicalInformation().toString(); } // globalInfo
/** * Returns a string describing classifier * * @return a description suitable for displaying in the explorer/experimenter * gui */ public String globalInfo() { return "Classifier for building 'logistic model trees', which are classification trees with " + "logistic regression functions at the leaves. The algorithm can deal with binary and multi-class " + "target variables, numeric and nominal attributes and missing values.\n\n" + "For more information see: \n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing this object * @return a description of the classifier suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "Class for performing a Bias-Variance decomposition on any classifier " + "using the method specified in:\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing classifier. * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "K-nearest neighbours classifier. Can " + "select appropriate value of K based on cross-validation. Can also do " + "distance weighting.\n\n" + "For more information, see\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing the kernel * * @return a description suitable for displaying in the explorer/experimenter * gui */ @Override public String globalInfo() { return "The Pearson VII function-based universal kernel.\n\n" + "For more information see:\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing classifier * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "Class for constructing a balanced forest of random trees.\n\n" + "For more information see: \n\n" + getTechnicalInformation().toString(); }
/** * Description to display in the GUI. * * @return the description */ @Override public String globalInfo() { return "Maps the output of a multi-label classifier to a known label combination using the hamming distance." + "For more information see:\n" + getTechnicalInformation().toString(); }
public String globalInfo() { return "Class implementing clustering-based multi-label classification." + " For more information, see\n\n" + getTechnicalInformation().toString(); } }
/** * Returns a string describing this class. * * @return a description suitable for displaying in a future gui */ public String globalInfo() { return "Class for calculating statistics of a multi-label dataset. " + "For more information, see\n\n" + getTechnicalInformation().toString(); }
public String globalInfo() { return "Class implementing the Hierarchy Of Multi-labEl leaRners " + "algorithm. For more information, see\n\n" + getTechnicalInformation().toString(); } }
/** * Returns a string describing the classifier. * * @return a string description of the classifier */ @Override public String globalInfo() { return "Class implementing the Classifier Chain (CC) algorithm." + "\n\n" + "For more information, see\n\n" + getTechnicalInformation().toString(); }
public String globalInfo() { return "Classs that implements RCut(Rank-based cut). It selects the k " + "top ranked labels for each instance, where k is a parameter " + "provided by the user or automatically tuned." + getTechnicalInformation().toString(); } }
/** * Global information about this estimator * * @return the global information for this estimator */ public String globalInfo() { return "Class for estimating an arbitrary quantile incrementally using " + "the P^2 algorithm. For more information see:\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing classifier * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "Class for construction a Rotation Forest. Can do classification " + "and regression depending on the base learner. \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 "Modified Diverse Density algorithm, with collective assumption.\n\n" + "More information about DD:\n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing classifier * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "Class for building and using a PRISM rule set for classification. " + "Can only deal with nominal attributes. Can't deal with missing values. " + "Doesn't do any pruning.\n\n" + "For more information, see \n\n" + getTechnicalInformation().toString(); }
/** * Returns a string describing classifier * * @return a description suitable for displaying in the explorer/experimenter * gui */ public String globalInfo() { return "MITI (Multi Instance Tree Inducer): multi-instance classification " + " based a decision tree learned using Blockeel et al.'s algorithm. For more " + "information, see\n\n" + getTechnicalInformation().toString(); }
/** * Description to display in the GUI. * * @return the description */ @Override public String globalInfo() { return "BR stacked with feature outputs.\nFor more information see:\n" + getTechnicalInformation().toString(); }